==> Synchronizing chroot copy [/home/alhp/workspace/chroot/root] -> [build_cf32b644-9579-4056-acc9-06524d6cb1d3]...done ==> Making package: python-statsmodels 0.15.0-1.1 (Sat Sep 12 11:34:28 2026) ==> Retrieving sources... -> Cloning statsmodels git repo... Cloning into bare repository '/home/alhp/workspace/build/x86-64-v3/python-statsmodels-0.15.0-1/statsmodels'... ==> Validating source files with sha256sums... statsmodels ... Passed Note: in a future version of systemd-nspawn the default set of permitted socket address families will be restricted to AF_INET, AF_INET6 and AF_UNIX. Use --restrict-address-families= to configure the set of permitted socket address families, or set RestrictAddressFamilies= in a .nspawn file. ==> Making package: python-statsmodels 0.15.0-1.1 (Sat Sep 12 09:34:40 2026) ==> Checking runtime dependencies... ==> Installing missing dependencies... resolving dependencies... looking for conflicting packages... Package (18) New Version Net Change extra/blas 3.12.1-2 0.74 MiB extra/cblas 3.12.1-2 0.34 MiB extra/lapack 3.12.1-2 15.06 MiB extra/python-certifi 2026.07.22-1 0.02 MiB extra/python-charset-normalizer 3.5.1-1 0.63 MiB extra/python-dateutil 2.9.0-8 1.03 MiB extra/python-idna 3.19-1 0.66 MiB extra/python-packaging 26.3-1 1.58 MiB extra/python-platformdirs 4.11.7-1 0.47 MiB extra/python-pooch 1.9.0-1 0.75 MiB extra/python-pytz 2026.1-1 0.17 MiB extra/python-requests 2.34.2-1 0.76 MiB extra/python-six 1.17.0-3 0.12 MiB extra/python-urllib3 2.7.0-1 1.43 MiB extra/python-numpy 2.5.3-1 49.33 MiB extra/python-pandas 2.3.3-6 110.38 MiB extra/python-patsy 1.0.3-1 2.23 MiB extra/python-scipy 1.18.1-1 118.60 MiB Total Installed Size: 304.29 MiB :: Proceed with installation? [Y/n] checking keyring... checking package integrity... loading package files... checking for file conflicts... :: Processing package changes... installing blas... installing cblas... installing lapack... installing python-numpy... Optional dependencies for python-numpy blas-openblas: faster linear algebra installing python-platformdirs... installing python-packaging... installing python-charset-normalizer... installing python-idna... installing python-urllib3... Optional dependencies for python-urllib3 python-brotli: Brotli support python-brotlicffi: Brotli support python-h2: HTTP/2 support python-pysocks: SOCKS support installing python-certifi... installing python-requests... Optional dependencies for python-requests python-chardet: alternative character encoding library python-pysocks: SOCKS proxy support installing python-pooch... Optional dependencies for python-pooch python-paramiko: for SFTP downloads python-tqdm: for printing a download progress bar installing python-scipy... Optional dependencies for python-scipy python-pillow: for image saving module installing python-six... installing python-dateutil... installing python-pytz... installing python-pandas... Optional dependencies for python-pandas python-pandas-datareader: pandas.io.data replacement (recommended) python-numexpr: accelerating certain numerical operations (recommended) python-bottleneck: accelerating certain types of nan evaluations (recommended) python-matplotlib: plotting python-jinja: conditional formatting with DataFrame.style python-tabulate: printing in Markdown-friendly format python-scipy: miscellaneous statistical functions [installed] python-numba: alternative execution engine python-xarray: pandas-like API for N-dimensional data python-xlrd: Excel XLS input python-xlwt: Excel XLS output python-openpyxl: Excel XLSX input/output python-xlsxwriter: alternative Excel XLSX output python-beautifulsoup4: read_html function (in any case) python-html5lib: read_html function (and/or python-lxml) python-lxml: read_xml, to_xml and read_html function (and/or python-html5lib) python-sqlalchemy: SQL database support python-psycopg2: PostgreSQL engine for sqlalchemy python-pymysql: MySQL engine for sqlalchemy python-pytables: HDF5-based reading / writing python-blosc: for msgpack compression using blosc zlib: compression for msgpack [installed] python-pyarrow: Parquet, ORC and feather reading/writing python-fsspec: handling files aside from local and HTTP python-qtpy: read_clipboard function (only one needed) xclip: read_clipboard function (only one needed) xsel: read_clipboard function (only one needed) python-brotli: Brotli compression python-snappy: Snappy compression python-zstandard: Zstandard (zstd) compression installing python-patsy... Optional dependencies for python-patsy python-scipy: needed for spline-related functions [installed] :: Running post-transaction hooks... (1/1) Arming ConditionNeedsUpdate... ==> Checking buildtime dependencies... ==> Installing missing dependencies... resolving dependencies... looking for conflicting packages... Package (67) New Version Net Change extra/aom 3.15.0-1 9.50 MiB extra/dav1d 1.5.4-1 1.85 MiB extra/freetype2 2.14.3-1 1.66 MiB extra/fribidi 1.0.16-2 0.24 MiB extra/graphite 1:1.3.15-1 0.20 MiB extra/harfbuzz 14.4.0-1 4.92 MiB extra/jbigkit 2.1-8 0.16 MiB extra/lcms2 2.19.1-1 0.69 MiB extra/libavif 1.4.2-1 0.87 MiB extra/libdeflate 1.26-1 0.14 MiB extra/libimagequant 4.4.1-2 0.60 MiB extra/libjpeg-turbo 3.2.0-2 2.65 MiB extra/libpng 1.6.58-2 0.58 MiB extra/libraqm 0.11.0-1 0.20 MiB extra/libtiff 4.7.2-1 1.32 MiB extra/libwebp 1.6.0-2 1.04 MiB extra/libxau 1.0.12-1 0.02 MiB extra/libxcb 1.17.0-1 3.87 MiB extra/libxdmcp 1.1.5-2 0.13 MiB extra/libyuv r2921+644251f25-1 1.50 MiB extra/meson 1.12.0-1 16.85 MiB extra/ninja 1.13.2-3 0.41 MiB extra/openjpeg2 2.5.4-1 13.37 MiB extra/patchelf 0.19.1-1 0.30 MiB extra/perl-error 0.17030-3 0.04 MiB extra/perl-mailtools 2.22-3 0.10 MiB extra/perl-timedate 2.35-1 0.15 MiB extra/python-autocommand 2.2.2-9 0.08 MiB extra/python-cloudpickle 3.1.2-3 0.18 MiB extra/python-contourpy 1.4.0-1 1.01 MiB extra/python-cycler 0.12.1-4 0.07 MiB extra/python-execnet 2.1.2-3 0.55 MiB extra/python-fonttools 4.65.0-1 21.56 MiB extra/python-iniconfig 2.3.0-1 0.07 MiB extra/python-jaraco.collections 5.1.0-3 0.11 MiB extra/python-jaraco.context 6.1.2-1 0.06 MiB extra/python-jaraco.functools 4.1.0-3 0.07 MiB extra/python-jaraco.text 4.0.0-4 0.08 MiB extra/python-kiwisolver 1.5.1-1 0.15 MiB extra/python-more-itertools 11.1.0-1 0.77 MiB extra/python-pillow 12.3.0-1 4.88 MiB extra/python-pluggy 1.6.0-3 0.23 MiB extra/python-pygments 2.21.0-1 15.59 MiB extra/python-pyparsing 3.3.2-1 1.55 MiB extra/python-pyproject-hooks 1.2.0-6 0.11 MiB extra/python-pyproject-metadata 0.9.0-3 0.19 MiB extra/python-setuptools 1:84.0.0-1 4.92 MiB extra/python-tqdm 4.70.1-1 0.64 MiB extra/python-vcs-versioning 2.3.4-1 1.18 MiB extra/qhull 2020.2-5 6.94 MiB extra/rav1e 0.8.1-3 7.49 MiB extra/svt-av1 4.2.0-1 5.36 MiB extra/xcb-proto 1.17.0-4 1.03 MiB extra/xorgproto 2025.1-1 1.47 MiB extra/zlib-ng 2.3.3-1 0.28 MiB extra/cython 3.2.9-1 19.14 MiB extra/git 2.55.0-1 31.33 MiB extra/meson-python 0.21.1-1 0.36 MiB extra/python-build 1.6.0-1 0.33 MiB extra/python-installer 1.0.1-1 0.21 MiB extra/python-joblib 1.6.0-2 2.81 MiB extra/python-matplotlib 3.11.2-1 32.45 MiB extra/python-pytest 1:9.1.1-1 4.95 MiB extra/python-pytest-randomly 5.0.0-1 0.05 MiB extra/python-pytest-xdist 3.8.0-3 0.56 MiB extra/python-setuptools-scm 10.2.3-1 0.23 MiB extra/python-wheel 0.48.0-1 0.34 MiB Total Installed Size: 232.74 MiB :: Proceed with installation? [Y/n] checking keyring... checking package integrity... loading package files... checking for file conflicts... :: Processing package changes... installing ninja... installing python-tqdm... Optional dependencies for python-tqdm python-requests: telegram [installed] installing meson... installing patchelf... installing python-pyproject-metadata... installing meson-python... Optional dependencies for meson-python python-colorama: colored output installing python-more-itertools... installing python-jaraco.functools... installing python-jaraco.context... installing python-autocommand... installing python-jaraco.text... Optional dependencies for python-jaraco.text python-inflect: for show-newlines script installing python-jaraco.collections... installing python-wheel... Optional dependencies for python-wheel python-keyring: for wheel.signatures python-xdg: for wheel.signatures python-setuptools: for legacy bdist_wheel subcommand [pending] installing python-setuptools... installing python-vcs-versioning... Optional dependencies for python-vcs-versioning python-rich: formatting of log messages installing python-setuptools-scm... Optional dependencies for python-setuptools-scm python-rich: use rich as console log handler installing python-pyproject-hooks... installing python-build... Optional dependencies for python-build python-pip: to use as the Python package installer (default) python-uv: to use as the Python package installer python-virtualenv: to use virtualenv for build isolation installing python-installer... installing python-pygments... installing cython... installing perl-error... installing perl-timedate... installing perl-mailtools... installing zlib-ng... installing git... Optional dependencies for git git-zsh-completion: upstream zsh completion tk: gitk and git gui openssh: ssh transport and crypto man: show help with `git command --help` perl-libwww: git svn perl-term-readkey: git svn and interactive.singlekey setting perl-io-socket-ssl: git send-email TLS support perl-authen-sasl: git send-email TLS support perl-cgi: gitweb (web interface) support python: git svn & git p4 [installed] subversion: git svn org.freedesktop.secrets: keyring credential helper libsecret: libsecret credential helper [installed] less: the default pager for git installing python-iniconfig... installing python-pluggy... installing python-pytest... installing python-pytest-randomly... installing python-execnet... installing python-pytest-xdist... Optional dependencies for python-pytest-xdist python-psutil: to use psutil for detection of the number of CPUs available python-setproctitle: to update the process title installing python-cloudpickle... installing python-joblib... Optional dependencies for python-joblib python-distributed: for dask parallel backend python-lz4: for compressed serialization python-numpy: for array manipulation [installed] python-psutil: to mitigate memory leaks in worker processes installing libpng... installing freetype2... Optional dependencies for freetype2 harfbuzz: Improved autohinting [pending] installing python-contourpy... Optional dependencies for python-contourpy python-matplotlib: matplotlib renderer [pending] installing python-cycler... installing python-fonttools... Optional dependencies for python-fonttools python-brotli: to compress/decompress WOFF 2.0 web fonts python-fs: to read/write UFO source files python-lxml: faster backend for XML files reading/writing python-lz4: for graphite type tables in ttLib/tables python-matplotlib: for visualizing DesignSpaceDocument and resulting VariationModel [pending] python-pyqt5: for drawing glyphs with Qt’s QPainterPath python-reportlab: to drawing glyphs as PNG images python-scipy: for finding wrong contour/component order between different masters [installed] python-sympy: for symbolic font statistics analysis python-uharfbuzz: to use the Harfbuzz Repacker for packing GSUB/GPOS tables python-unicodedata2: for displaying the Unicode character names when dumping the cmap table with ttx python-zopfli: faster backend fom WOFF 1.0 web fonts compression installing python-kiwisolver... installing libjpeg-turbo... installing jbigkit... installing libdeflate... installing libwebp... Optional dependencies for libwebp libwebp-utils: WebP conversion and inspection tools installing libtiff... Optional dependencies for libtiff freeglut: for using tiffgt installing lcms2... installing aom... installing dav1d... Optional dependencies for dav1d dav1d-doc: HTML documentation installing libyuv... installing rav1e... installing svt-av1... installing libavif... installing fribidi... installing graphite... Optional dependencies for graphite graphite-docs: Documentation installing harfbuzz... Optional dependencies for harfbuzz harfbuzz-utils: utilities installing libraqm... installing openjpeg2... installing libimagequant... installing xcb-proto... installing xorgproto... installing libxdmcp... installing libxau... installing libxcb... installing python-pillow... Optional dependencies for python-pillow libwebp: for webp images [installed] tk: for the ImageTK module python-olefile: OLE2 file support python-pyqt6: for the ImageQt module python-defusedxml: for reading XMP tags installing python-pyparsing... Optional dependencies for python-pyparsing python-railroad-diagrams: for generating Railroad Diagrams python-jinja: for generating Railroad Diagrams installing qhull... installing python-matplotlib... Optional dependencies for python-matplotlib tk: Tk{Agg,Cairo} backends pyside6: alternative for Qt6{Agg,Cairo} backends python-pyqt6: Qt6{Agg,Cairo} backends python-gobject: for GTK{3,4}{Agg,Cairo} backend python-wxpython: WX{Agg,Cairo} backend python-cairo: {GTK{3,4},Qt{5,6},Tk,WX}Cairo backends python-cairocffi: alternative for Cairo backends python-tornado: WebAgg backend ffmpeg: for saving movies imagemagick: for saving animated gifs ghostscript: usetex dependencies texlive-binextra: usetex dependencies texlive-fontsrecommended: usetex dependencies texlive-latexrecommended: usetex usage with pdflatex python-certifi: https support [installed] :: Running post-transaction hooks... (1/3) Creating system user accounts... Creating group 'git' with GID 969. Creating user 'git' (git daemon user) with UID 969 and GID 969. (2/3) Reloading system manager configuration... Skipped: Current root is not booted. (3/3) Arming ConditionNeedsUpdate... ==> Retrieving sources... ==> WARNING: Skipping all source file integrity checks. ==> Extracting sources... -> Creating working copy of statsmodels git repo... Cloning into 'statsmodels'... done. Switched to a new branch 'makepkg' ==> Starting prepare()... ==> Starting build()... * Getting build dependencies for wheel... * Building wheel... + meson setup /startdir/src/statsmodels /startdir/src/statsmodels/.mesonpy-162xzq6o -Dbuildtype=release -Db_ndebug=if-release -Db_vscrt=md --vsenv --native-file=/startdir/src/statsmodels/.mesonpy-162xzq6o/meson-python-native-file.ini The Meson build system Version: 1.12.0 Source dir: /startdir/src/statsmodels Build dir: /startdir/src/statsmodels/.mesonpy-162xzq6o Build type: native build Project name: statsmodels Project version: 0.15.1.dev0+g278ff9950.d20260912 C compiler for the host machine: cc (gcc 16.2.1 "cc (GCC) 16.2.1 20260810") C linker for the host machine: cc ld.bfd 2.47 Cython compiler for the host machine: cython (cython 3.2.9) Host machine cpu family: x86_64 Host machine cpu: x86_64 Program cython found: YES (/usr/bin/cython) Program statsmodels/_build/tempita.py found: YES (/usr/bin/python /startdir/src/statsmodels/statsmodels/_build/tempita.py) Checking if "scipy cython_blas blas_int" compiles: YES Library m found: YES Program python found: YES (/usr/bin/python) Found pkg-config: YES (/usr/bin/pkg-config) 3.0.7 Run-time dependency python found: YES 3.14 Configuring _blas_int.pxi using configuration ../statsmodels/meson.build:101: WARNING: Project targets '>= 1.9.0' but uses feature deprecated since '0.60.0': install_subdir with empty directory. It worked by accident and is buggy. Use install_emptydir instead. Build targets in project: 69 WARNING: Deprecated features used: * 0.60.0: {'install_subdir with empty directory'} statsmodels 0.15.1.dev0+g278ff9950.d20260912 User defined options Native files: /startdir/src/statsmodels/.mesonpy-162xzq6o/meson-python-native-file.ini b_ndebug : if-release b_vscrt : md buildtype : release vsenv : true Found ninja-1.13.2 at /usr/bin/ninja Visual Studio environment is needed to run Ninja. It is recommended to use Meson wrapper: /usr/bin/meson compile -C . Generating targets: 0%| | 0/69 eta ? Writing build.ninja: 0%| | 0/173 eta ? + /usr/bin/ninja [1/121] Copying file statsmodels/tsa/__init__.py [2/121] Copying file statsmodels/tsa/statespace/_kalman_smoother.pxd [3/121] Copying file statsmodels/tsa/statespace/_filters/__init__.py [4/121] Copying file statsmodels/tsa/statespace/_filters/_inversions.pxd [5/121] Generating statsmodels/tsa/innovations/_arma_innovations_pyx with a custom command [6/121] Generating statsmodels/tsa/regime_switching/_hamilton_filter_pyx with a custom command [7/121] Copying file statsmodels/tsa/statespace/_cfa_simulation_smoother.pxd [8/121] Copying file statsmodels/tsa/statespace/_simulation_smoother.pxd [9/121] Copying file statsmodels/tsa/statespace/_tools.pxd [10/121] Copying file statsmodels/tsa/statespace/_filters/_conventional.pxd [11/121] Copying file statsmodels/tsa/statespace/_filters/_univariate_diffuse.pxd [12/121] Copying file statsmodels/tsa/statespace/_filters/_univariate.pxd [13/121] Copying file statsmodels/tsa/statespace/_smoothers/__init__.py [14/121] Copying file statsmodels/tsa/statespace/_smoothers/_alternative.pxd [15/121] Copying file statsmodels/includes/math.pxd [16/121] Generating statsmodels/tsa/regime_switching/_kim_smoother_pyx with a custom command [17/121] Copying file statsmodels/tsa/statespace/__init__.py [18/121] Copying file statsmodels/tsa/statespace/_initialization.pxd [19/121] Copying file statsmodels/tsa/statespace/_representation.pxd [20/121] Generating statsmodels/tsa/statespace/_filters/_conventional_pyx with a custom command [21/121] Generating statsmodels/tsa/statespace/_filters/_inversions_pyx with a custom command [22/121] Generating statsmodels/tsa/statespace/_filters/_univariate_diffuse_pyx with a custom command [23/121] Generating statsmodels/tsa/statespace/_filters/_univariate_pyx with a custom command [24/121] Copying file statsmodels/__init__.py [25/121] Copying file statsmodels/includes/__init__.pxd [26/121] Copying file statsmodels/tsa/statespace/_kalman_filter.pxd [27/121] Copying file statsmodels/tsa/statespace/_smoothers/_classical.pxd [28/121] Copying file statsmodels/tsa/statespace/_smoothers/_conventional.pxd [29/121] Copying file statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pxd [30/121] Generating statsmodels/tsa/statespace/_smoothers/_alternative_pyx with a custom command [31/121] Copying file statsmodels/tsa/statespace/_smoothers/_univariate.pxd [32/121] Generating statsmodels/tsa/statespace/_smoothers/_classical_pyx with a custom command [33/121] Generating statsmodels/tsa/statespace/_cfa_simulation_smoother_pyx with a custom command [34/121] Generating statsmodels/tsa/statespace/_representation_pyx with a custom command [35/121] Generating statsmodels/tsa/statespace/_simulation_smoother_pyx with a custom command [36/121] Generating statsmodels/tsa/statespace/_smoothers/_conventional_pyx with a custom command [37/121] Generating statsmodels/tsa/statespace/_smoothers/_univariate_diffuse_pyx with a custom command [38/121] Generating statsmodels/tsa/statespace/_kalman_filter_pyx with a custom command [39/121] Generating statsmodels/tsa/statespace/_kalman_smoother_pyx with a custom command [40/121] Generating statsmodels/tsa/statespace/_smoothers/_univariate_pyx with a custom command [41/121] Generating statsmodels/tsa/statespace/_initialization_pyx with a custom command [42/121] Generating statsmodels/tsa/statespace/_tools_pyx with a custom command [43/121] Generating statsmodels/generate-version with a custom command [44/121] Compiling Cython source /startdir/src/statsmodels/statsmodels/nonparametric/linbin.pyx [45/121] Compiling Cython source /startdir/src/statsmodels/statsmodels/robust/_qn.pyx [46/121] Compiling Cython source /startdir/src/statsmodels/statsmodels/tsa/_innovations.pyx [47/121] Compiling Cython source /startdir/src/statsmodels/statsmodels/tsa/stl/_stl.pyx [48/121] Compiling C object statsmodels/nonparametric/linbin.cpython-314-x86_64-linux-gnu.so.p/meson-generated_linbin.pyx.c.o [49/121] Compiling Cython source /startdir/src/statsmodels/statsmodels/nonparametric/_smoothers_lowess.pyx [50/121] Generating 'statsmodels/tsa/regime_switching/_kim_smoother.cpython-314-x86_64-linux-gnu.so.p/_kim_smoother.c' [51/121] Generating 'statsmodels/tsa/regime_switching/_hamilton_filter.cpython-314-x86_64-linux-gnu.so.p/_hamilton_filter.c' [52/121] Compiling Cython source /startdir/src/statsmodels/statsmodels/tsa/holtwinters/_exponential_smoothers.pyx [53/121] Generating 'statsmodels/tsa/statespace/_smoothers/_alternative.cpython-314-x86_64-linux-gnu.so.p/_alternative.c' [54/121] Generating 'statsmodels/tsa/innovations/_arma_innovations.cpython-314-x86_64-linux-gnu.so.p/_arma_innovations.c' [55/121] Compiling Cython source /startdir/src/statsmodels/statsmodels/tsa/exponential_smoothing/_ets_smooth.pyx [56/121] Generating 'statsmodels/tsa/statespace/_smoothers/_univariate.cpython-314-x86_64-linux-gnu.so.p/_univariate.c' [57/121] Generating 'statsmodels/tsa/statespace/_smoothers/_conventional.cpython-314-x86_64-linux-gnu.so.p/_conventional.c' [58/121] Generating 'statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.cpython-314-x86_64-linux-gnu.so.p/_univariate_diffuse.c' warning: statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx:588:14: Unreachable code warning: statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx:1195:14: Unreachable code warning: statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx:1802:14: Unreachable code warning: statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx:2409:14: Unreachable code [59/121] Compiling C object statsmodels/robust/_qn.cpython-314-x86_64-linux-gnu.so.p/meson-generated__qn.pyx.c.o [60/121] Compiling C object statsmodels/nonparametric/_smoothers_lowess.cpython-314-x86_64-linux-gnu.so.p/meson-generated__smoothers_lowess.pyx.c.o [61/121] Compiling C object statsmodels/tsa/_innovations.cpython-314-x86_64-linux-gnu.so.p/meson-generated__innovations.pyx.c.o [62/121] Generating 'statsmodels/tsa/statespace/_kalman_smoother.cpython-314-x86_64-linux-gnu.so.p/_kalman_smoother.c' [63/121] Compiling C object statsmodels/tsa/stl/_stl.cpython-314-x86_64-linux-gnu.so.p/meson-generated__stl.pyx.c.o [64/121] Compiling C object statsmodels/tsa/statespace/_smoothers/_alternative.cpython-314-x86_64-linux-gnu.so.p/meson-generated__alternative.c.o [65/121] Linking target statsmodels/nonparametric/linbin.cpython-314-x86_64-linux-gnu.so [66/121] Compiling C object statsmodels/tsa/regime_switching/_kim_smoother.cpython-314-x86_64-linux-gnu.so.p/meson-generated__kim_smoother.c.o [67/121] Generating 'statsmodels/tsa/statespace/_filters/_inversions.cpython-314-x86_64-linux-gnu.so.p/_inversions.c' [68/121] Generating 'statsmodels/tsa/statespace/_filters/_univariate_diffuse.cpython-314-x86_64-linux-gnu.so.p/_univariate_diffuse.c' [69/121] Generating 'statsmodels/tsa/statespace/_smoothers/_classical.cpython-314-x86_64-linux-gnu.so.p/_classical.c' [70/121] Generating 'statsmodels/tsa/statespace/_filters/_conventional.cpython-314-x86_64-linux-gnu.so.p/_conventional.c' [71/121] Generating 'statsmodels/tsa/statespace/_filters/_univariate.cpython-314-x86_64-linux-gnu.so.p/_univariate.c' [72/121] Generating 'statsmodels/tsa/statespace/_initialization.cpython-314-x86_64-linux-gnu.so.p/_initialization.c' [73/121] Compiling C object statsmodels/tsa/regime_switching/_hamilton_filter.cpython-314-x86_64-linux-gnu.so.p/meson-generated__hamilton_filter.c.o [74/121] Compiling C object statsmodels/tsa/statespace/_smoothers/_univariate.cpython-314-x86_64-linux-gnu.so.p/meson-generated__univariate.c.o [75/121] Compiling C object statsmodels/tsa/holtwinters/_exponential_smoothers.cpython-314-x86_64-linux-gnu.so.p/meson-generated__exponential_smoothers.pyx.c.o [76/121] Compiling C object statsmodels/tsa/statespace/_smoothers/_conventional.cpython-314-x86_64-linux-gnu.so.p/meson-generated__conventional.c.o [77/121] Generating 'statsmodels/tsa/statespace/_cfa_simulation_smoother.cpython-314-x86_64-linux-gnu.so.p/_cfa_simulation_smoother.c' [78/121] Generating 'statsmodels/tsa/statespace/_simulation_smoother.cpython-314-x86_64-linux-gnu.so.p/_simulation_smoother.c' [79/121] Compiling C object statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.cpython-314-x86_64-linux-gnu.so.p/meson-generated__univariate_diffuse.c.o [80/121] Generating 'statsmodels/tsa/statespace/_representation.cpython-314-x86_64-linux-gnu.so.p/_representation.c' [81/121] Compiling C object statsmodels/tsa/innovations/_arma_innovations.cpython-314-x86_64-linux-gnu.so.p/meson-generated__arma_innovations.c.o [82/121] Compiling C object statsmodels/tsa/statespace/_filters/_univariate_diffuse.cpython-314-x86_64-linux-gnu.so.p/meson-generated__univariate_diffuse.c.o [83/121] Compiling C object statsmodels/tsa/statespace/_filters/_conventional.cpython-314-x86_64-linux-gnu.so.p/meson-generated__conventional.c.o [84/121] Compiling C object statsmodels/tsa/statespace/_smoothers/_classical.cpython-314-x86_64-linux-gnu.so.p/meson-generated__classical.c.o [85/121] Compiling C object statsmodels/tsa/statespace/_filters/_inversions.cpython-314-x86_64-linux-gnu.so.p/meson-generated__inversions.c.o [86/121] Compiling C object statsmodels/tsa/statespace/_filters/_univariate.cpython-314-x86_64-linux-gnu.so.p/meson-generated__univariate.c.o [87/121] Generating 'statsmodels/tsa/statespace/_tools.cpython-314-x86_64-linux-gnu.so.p/_tools.c' [88/121] Compiling C object statsmodels/tsa/statespace/_initialization.cpython-314-x86_64-linux-gnu.so.p/meson-generated__initialization.c.o [89/121] Compiling C object statsmodels/tsa/statespace/_kalman_smoother.cpython-314-x86_64-linux-gnu.so.p/meson-generated__kalman_smoother.c.o [90/121] Generating 'statsmodels/tsa/statespace/_kalman_filter.cpython-314-x86_64-linux-gnu.so.p/_kalman_filter.c' [91/121] Compiling C object statsmodels/tsa/exponential_smoothing/_ets_smooth.cpython-314-x86_64-linux-gnu.so.p/meson-generated__ets_smooth.pyx.c.o [92/121] Linking target statsmodels/nonparametric/_smoothers_lowess.cpython-314-x86_64-linux-gnu.so [93/121] Linking target statsmodels/tsa/statespace/_smoothers/_alternative.cpython-314-x86_64-linux-gnu.so [94/121] Compiling C object statsmodels/tsa/statespace/_cfa_simulation_smoother.cpython-314-x86_64-linux-gnu.so.p/meson-generated__cfa_simulation_smoother.c.o [95/121] Linking target statsmodels/tsa/regime_switching/_kim_smoother.cpython-314-x86_64-linux-gnu.so [96/121] Linking target statsmodels/tsa/_innovations.cpython-314-x86_64-linux-gnu.so [97/121] Linking target statsmodels/robust/_qn.cpython-314-x86_64-linux-gnu.so [98/121] Linking target statsmodels/tsa/holtwinters/_exponential_smoothers.cpython-314-x86_64-linux-gnu.so [99/121] Compiling C object statsmodels/tsa/statespace/_representation.cpython-314-x86_64-linux-gnu.so.p/meson-generated__representation.c.o [100/121] Linking target statsmodels/tsa/innovations/_arma_innovations.cpython-314-x86_64-linux-gnu.so [101/121] Compiling C object statsmodels/tsa/statespace/_tools.cpython-314-x86_64-linux-gnu.so.p/meson-generated__tools.c.o statsmodels/tsa/statespace/_tools.cpython-314-x86_64-linux-gnu.so.p/_tools.c:54408:55: warning: ‘__pyx_f_11statsmodels_3tsa_10statespace_6_tools__zselect2’ defined but not used [-Wunused-function] 54408 | static __pyx_t_5scipy_6linalg_11cython_blas_blas_bint __pyx_f_11statsmodels_3tsa_10statespace_6_tools__zselect2(CYTHON_UNUSED __pyx_t_double_complex *__pyx_v_a, CYTHON_UNUSED __pyx_t_double_complex *__pyx_v_b) { | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ statsmodels/tsa/statespace/_tools.cpython-314-x86_64-linux-gnu.so.p/_tools.c:43614:55: warning: ‘__pyx_f_11statsmodels_3tsa_10statespace_6_tools__cselect2’ defined but not used [-Wunused-function] 43614 | static __pyx_t_5scipy_6linalg_11cython_blas_blas_bint __pyx_f_11statsmodels_3tsa_10statespace_6_tools__cselect2(CYTHON_UNUSED __pyx_t_float_complex *__pyx_v_a, CYTHON_UNUSED __pyx_t_float_complex *__pyx_v_b) { | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ statsmodels/tsa/statespace/_tools.cpython-314-x86_64-linux-gnu.so.p/_tools.c:32974:55: warning: ‘__pyx_f_11statsmodels_3tsa_10statespace_6_tools__dselect1’ defined but not used [-Wunused-function] 32974 | static __pyx_t_5scipy_6linalg_11cython_blas_blas_bint __pyx_f_11statsmodels_3tsa_10statespace_6_tools__dselect1(CYTHON_UNUSED __pyx_t_5numpy_float64_t *__pyx_v_a) { | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ statsmodels/tsa/statespace/_tools.cpython-314-x86_64-linux-gnu.so.p/_tools.c:22352:55: warning: ‘__pyx_f_11statsmodels_3tsa_10statespace_6_tools__sselect1’ defined but not used [-Wunused-function] 22352 | static __pyx_t_5scipy_6linalg_11cython_blas_blas_bint __pyx_f_11statsmodels_3tsa_10statespace_6_tools__sselect1(CYTHON_UNUSED __pyx_t_5numpy_float32_t *__pyx_v_a) { | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ [102/121] Linking target statsmodels/tsa/statespace/_smoothers/_univariate.cpython-314-x86_64-linux-gnu.so [103/121] Compiling C object statsmodels/tsa/statespace/_simulation_smoother.cpython-314-x86_64-linux-gnu.so.p/meson-generated__simulation_smoother.c.o [104/121] Linking target statsmodels/tsa/stl/_stl.cpython-314-x86_64-linux-gnu.so [105/121] Linking target statsmodels/tsa/regime_switching/_hamilton_filter.cpython-314-x86_64-linux-gnu.so [106/121] Linking target statsmodels/tsa/statespace/_filters/_univariate_diffuse.cpython-314-x86_64-linux-gnu.so [107/121] Linking target statsmodels/tsa/statespace/_initialization.cpython-314-x86_64-linux-gnu.so [108/121] Linking target statsmodels/tsa/statespace/_filters/_inversions.cpython-314-x86_64-linux-gnu.so [109/121] Linking target statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.cpython-314-x86_64-linux-gnu.so [110/121] Linking target statsmodels/tsa/statespace/_smoothers/_conventional.cpython-314-x86_64-linux-gnu.so [111/121] Linking target statsmodels/tsa/statespace/_filters/_conventional.cpython-314-x86_64-linux-gnu.so [112/121] Linking target statsmodels/tsa/statespace/_smoothers/_classical.cpython-314-x86_64-linux-gnu.so [113/121] Linking target statsmodels/tsa/statespace/_filters/_univariate.cpython-314-x86_64-linux-gnu.so [114/121] Linking target statsmodels/tsa/statespace/_kalman_smoother.cpython-314-x86_64-linux-gnu.so [115/121] Compiling C object statsmodels/tsa/statespace/_kalman_filter.cpython-314-x86_64-linux-gnu.so.p/meson-generated__kalman_filter.c.o [116/121] Linking target statsmodels/tsa/exponential_smoothing/_ets_smooth.cpython-314-x86_64-linux-gnu.so [117/121] Linking target statsmodels/tsa/statespace/_cfa_simulation_smoother.cpython-314-x86_64-linux-gnu.so [118/121] Linking target statsmodels/tsa/statespace/_tools.cpython-314-x86_64-linux-gnu.so [119/121] Linking target statsmodels/tsa/statespace/_simulation_smoother.cpython-314-x86_64-linux-gnu.so [120/121] Linking target statsmodels/tsa/statespace/_representation.cpython-314-x86_64-linux-gnu.so [121/121] Linking target statsmodels/tsa/statespace/_kalman_filter.cpython-314-x86_64-linux-gnu.so [1/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/_version.py [2/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/robust/_qn.cpython-314-x86_64-linux-gnu.so [3/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/nonparametric/_smoothers_lowess.cpython-314-x86_64-linux-gnu.so [4/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/nonparametric/linbin.cpython-314-x86_64-linux-gnu.so [5/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/_innovations.cpython-314-x86_64-linux-gnu.so [6/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/exponential_smoothing/_ets_smooth.cpython-314-x86_64-linux-gnu.so [7/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/holtwinters/_exponential_smoothers.cpython-314-x86_64-linux-gnu.so [8/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/innovations/_arma_innovations.cpython-314-x86_64-linux-gnu.so [9/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/regime_switching/_hamilton_filter.cpython-314-x86_64-linux-gnu.so [10/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/regime_switching/_kim_smoother.cpython-314-x86_64-linux-gnu.so [11/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_filters/_conventional.cpython-314-x86_64-linux-gnu.so [12/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_filters/_inversions.cpython-314-x86_64-linux-gnu.so [13/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_filters/_univariate_diffuse.cpython-314-x86_64-linux-gnu.so [14/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_filters/_univariate.cpython-314-x86_64-linux-gnu.so [15/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_smoothers/_alternative.cpython-314-x86_64-linux-gnu.so [16/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_smoothers/_classical.cpython-314-x86_64-linux-gnu.so [17/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_smoothers/_conventional.cpython-314-x86_64-linux-gnu.so [18/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.cpython-314-x86_64-linux-gnu.so [19/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_smoothers/_univariate.cpython-314-x86_64-linux-gnu.so [20/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_cfa_simulation_smoother.cpython-314-x86_64-linux-gnu.so [21/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_initialization.cpython-314-x86_64-linux-gnu.so [22/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_kalman_filter.cpython-314-x86_64-linux-gnu.so [23/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_kalman_smoother.cpython-314-x86_64-linux-gnu.so [24/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_representation.cpython-314-x86_64-linux-gnu.so [25/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_simulation_smoother.cpython-314-x86_64-linux-gnu.so [26/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/statespace/_tools.cpython-314-x86_64-linux-gnu.so [27/1565] /startdir/src/statsmodels/.mesonpy-162xzq6o/statsmodels/tsa/stl/_stl.cpython-314-x86_64-linux-gnu.so [28/1565] /startdir/src/statsmodels/pyproject.toml [29/1565] /startdir/src/statsmodels/statsmodels/__init__.py [30/1565] /startdir/src/statsmodels/statsmodels/api.py [31/1565] /startdir/src/statsmodels/statsmodels/conftest.py [32/1565] /startdir/src/statsmodels/statsmodels/base/__init__.py [33/1565] /startdir/src/statsmodels/statsmodels/base/_constraints.py [34/1565] /startdir/src/statsmodels/statsmodels/base/_parameter_inference.py [35/1565] /startdir/src/statsmodels/statsmodels/base/_penalized.py [36/1565] /startdir/src/statsmodels/statsmodels/base/_penalties.py [37/1565] /startdir/src/statsmodels/statsmodels/base/_prediction_inference.py [38/1565] /startdir/src/statsmodels/statsmodels/base/_screening.py [39/1565] /startdir/src/statsmodels/statsmodels/base/covtype.py [40/1565] /startdir/src/statsmodels/statsmodels/base/data.py [41/1565] /startdir/src/statsmodels/statsmodels/base/distributed_estimation.py [42/1565] /startdir/src/statsmodels/statsmodels/base/elastic_net.py [43/1565] /startdir/src/statsmodels/statsmodels/base/l1_cvxopt.py [44/1565] /startdir/src/statsmodels/statsmodels/base/l1_slsqp.py [45/1565] /startdir/src/statsmodels/statsmodels/base/l1_solvers_common.py [46/1565] /startdir/src/statsmodels/statsmodels/base/model.py [47/1565] /startdir/src/statsmodels/statsmodels/base/optimizer.py [48/1565] /startdir/src/statsmodels/statsmodels/base/transform.py [49/1565] /startdir/src/statsmodels/statsmodels/base/wrapper.py [50/1565] /startdir/src/statsmodels/statsmodels/base/tests/__init__.py [51/1565] /startdir/src/statsmodels/statsmodels/base/tests/test_constraints.py [52/1565] /startdir/src/statsmodels/statsmodels/base/tests/test_data.py [53/1565] /startdir/src/statsmodels/statsmodels/base/tests/test_distributed_estimation.py [54/1565] /startdir/src/statsmodels/statsmodels/base/tests/test_generic_methods.py [55/1565] /startdir/src/statsmodels/statsmodels/base/tests/test_optimize.py [56/1565] /startdir/src/statsmodels/statsmodels/base/tests/test_penalized.py [57/1565] /startdir/src/statsmodels/statsmodels/base/tests/test_penalties.py [58/1565] /startdir/src/statsmodels/statsmodels/base/tests/test_polars_compat.py [59/1565] /startdir/src/statsmodels/statsmodels/base/tests/test_predict.py [60/1565] /startdir/src/statsmodels/statsmodels/base/tests/test_screening.py [61/1565] /startdir/src/statsmodels/statsmodels/base/tests/test_shrink_pickle.py [62/1565] /startdir/src/statsmodels/statsmodels/base/tests/test_transform.py [63/1565] /startdir/src/statsmodels/statsmodels/compat/__init__.py [64/1565] /startdir/src/statsmodels/statsmodels/compat/matplotlib.py [65/1565] /startdir/src/statsmodels/statsmodels/compat/numpy.py [66/1565] /startdir/src/statsmodels/statsmodels/compat/pandas.py [67/1565] /startdir/src/statsmodels/statsmodels/compat/patsy.py [68/1565] /startdir/src/statsmodels/statsmodels/compat/platform.py [69/1565] /startdir/src/statsmodels/statsmodels/compat/pytest.py [70/1565] /startdir/src/statsmodels/statsmodels/compat/python.py [71/1565] /startdir/src/statsmodels/statsmodels/compat/scipy.py [72/1565] /startdir/src/statsmodels/statsmodels/compat/tests/__init__.py [73/1565] /startdir/src/statsmodels/statsmodels/compat/tests/test_itercompat.py [74/1565] /startdir/src/statsmodels/statsmodels/compat/tests/test_pandas.py [75/1565] /startdir/src/statsmodels/statsmodels/compat/tests/test_scipy_compat.py [76/1565] /startdir/src/statsmodels/statsmodels/datasets/__init__.py [77/1565] /startdir/src/statsmodels/statsmodels/datasets/template_data.py [78/1565] /startdir/src/statsmodels/statsmodels/datasets/utils.py [79/1565] /startdir/src/statsmodels/statsmodels/datasets/anes96/__init__.py [80/1565] /startdir/src/statsmodels/statsmodels/datasets/anes96/anes96.csv [81/1565] /startdir/src/statsmodels/statsmodels/datasets/anes96/data.py [82/1565] /startdir/src/statsmodels/statsmodels/datasets/anes96/src/anes96.csv [83/1565] /startdir/src/statsmodels/statsmodels/datasets/cancer/__init__.py [84/1565] /startdir/src/statsmodels/statsmodels/datasets/cancer/cancer.csv [85/1565] /startdir/src/statsmodels/statsmodels/datasets/cancer/data.py [86/1565] /startdir/src/statsmodels/statsmodels/datasets/ccard/R_wls.s [87/1565] /startdir/src/statsmodels/statsmodels/datasets/ccard/__init__.py [88/1565] /startdir/src/statsmodels/statsmodels/datasets/ccard/ccard.csv [89/1565] /startdir/src/statsmodels/statsmodels/datasets/ccard/data.py [90/1565] /startdir/src/statsmodels/statsmodels/datasets/ccard/src/ccard.csv [91/1565] /startdir/src/statsmodels/statsmodels/datasets/ccard/src/names.txt [92/1565] /startdir/src/statsmodels/statsmodels/datasets/china_smoking/__init__.py [93/1565] /startdir/src/statsmodels/statsmodels/datasets/china_smoking/china_smoking.csv [94/1565] /startdir/src/statsmodels/statsmodels/datasets/china_smoking/data.py [95/1565] /startdir/src/statsmodels/statsmodels/datasets/co2/__init__.py [96/1565] /startdir/src/statsmodels/statsmodels/datasets/co2/co2.csv [97/1565] /startdir/src/statsmodels/statsmodels/datasets/co2/data.py [98/1565] /startdir/src/statsmodels/statsmodels/datasets/co2/src/maunaloa_c.dat [99/1565] /startdir/src/statsmodels/statsmodels/datasets/committee/R_committee.s [100/1565] /startdir/src/statsmodels/statsmodels/datasets/committee/__init__.py [101/1565] /startdir/src/statsmodels/statsmodels/datasets/committee/committee.csv [102/1565] /startdir/src/statsmodels/statsmodels/datasets/committee/data.py [103/1565] /startdir/src/statsmodels/statsmodels/datasets/committee/src/committee.dat [104/1565] /startdir/src/statsmodels/statsmodels/datasets/copper/__init__.py [105/1565] /startdir/src/statsmodels/statsmodels/datasets/copper/copper.csv [106/1565] /startdir/src/statsmodels/statsmodels/datasets/copper/data.py [107/1565] /startdir/src/statsmodels/statsmodels/datasets/copper/src/copper.dat [108/1565] /startdir/src/statsmodels/statsmodels/datasets/cpunish/R_cpunish.s [109/1565] /startdir/src/statsmodels/statsmodels/datasets/cpunish/__init__.py [110/1565] /startdir/src/statsmodels/statsmodels/datasets/cpunish/cpunish.csv [111/1565] /startdir/src/statsmodels/statsmodels/datasets/cpunish/data.py [112/1565] /startdir/src/statsmodels/statsmodels/datasets/cpunish/src/cpunish.dat [113/1565] /startdir/src/statsmodels/statsmodels/datasets/danish_data/__init__.py [114/1565] /startdir/src/statsmodels/statsmodels/datasets/danish_data/data.csv [115/1565] /startdir/src/statsmodels/statsmodels/datasets/danish_data/data.py [116/1565] /startdir/src/statsmodels/statsmodels/datasets/elec_equip/__init__.py [117/1565] /startdir/src/statsmodels/statsmodels/datasets/elec_equip/data.py [118/1565] /startdir/src/statsmodels/statsmodels/datasets/elec_equip/elec_equip.csv [119/1565] /startdir/src/statsmodels/statsmodels/datasets/elnino/__init__.py [120/1565] /startdir/src/statsmodels/statsmodels/datasets/elnino/data.py [121/1565] /startdir/src/statsmodels/statsmodels/datasets/elnino/elnino.csv [122/1565] /startdir/src/statsmodels/statsmodels/datasets/elnino/src/elnino.dat [123/1565] /startdir/src/statsmodels/statsmodels/datasets/engel/__init__.py [124/1565] /startdir/src/statsmodels/statsmodels/datasets/engel/data.py [125/1565] /startdir/src/statsmodels/statsmodels/datasets/engel/engel.csv [126/1565] /startdir/src/statsmodels/statsmodels/datasets/fair/__init__.py 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statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonPwNr::test_basic XFAIL [ 4%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmTweedieAwNr::test_pearson_chi2 PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmTweedieAwNr::test_residuals PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmTweedieAwNr::test_basic PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmTweedieAwNr::test_getprediction PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmTweedieAwNr::test_compare_optimizers PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianAwNr::test_residuals PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianAwNr::test_compare_optimizers PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianAwNr::test_pearson_chi2 PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianAwNr::test_basic PASSED [ 4%] 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statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[0-Binomial-Probit] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[1-Poisson-Identity] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[0-NegativeBinomial-Log] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[0-Gamma-Log] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[0-Binomial-Cauchy] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[0-Poisson-Sqrt] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[0-Gaussian-Identity] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[1-Binomial-Probit] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[1-Poisson-Log] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[0-Gaussian-Log] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[1-NegativeBinomial-Identity] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[0-NegativeBinomial-Identity] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[1-InverseGaussian-Identity] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[1-Binomial-Log] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[1-Gamma-Identity] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[0-Poisson-Identity] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[0-Binomial-CLogLog] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[0-Gaussian-InversePower] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[0-NegativeBinomial-InversePower] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[1-InverseGaussian-Log] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[0-Gamma-InversePower] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[0-InverseGaussian-Identity] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[0-InverseGaussian-Log] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[1-Binomial-Logit] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls[1-Gaussian-Identity] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_weights_different_formats[list] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_warnings_raised PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_weights_different_formats[Series] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_weights_different_formats[ndarray] PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_poisson_residuals PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::test_incompatible_input PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwNr::test_basic PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwNr::test_compare_optimizers PASSED [ 4%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwNr::test_getprediction PASSED [ 5%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwNr::test_pearson_chi2 PASSED [ 5%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwNr::test_residuals PASSED [ 5%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwHC::test_basic PASSED [ 5%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwHC::test_residuals PASSED [ 5%] statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwHC::test_getprediction PASSED [ 5%] 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statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_nobs_diffuse PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_measurement_disturbance PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_forecasts_error_cov PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_state_cov PASSED [ 5%] 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statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_filtered_state_cov PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_kalman_gain PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_predicted_state PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothing_error SKIPPED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_forecasts PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_simulation_smoothed_state XFAIL [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_state_disturbance PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_filtered_state PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_loglike PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_state_disturbance_cov PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_initialization PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_forecasts_error_cov PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_state_cov PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_state PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLevelAnalytic::test_results PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_state_autocov PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_filtered_state PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_loglike PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_initialization PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_forecasts PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_state_cov PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_forecasts_error_diffuse_cov PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_state PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_forecasts_error PASSED [ 5%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_predicted_diffuse_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_filtered_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_state_disturbance_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_measurement_disturbance PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_predicted_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_simulation_smoothed_state XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_initialization_approx PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_kalman_gain PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_scaled_smoothed_estimator PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_state_disturbance PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_forecasts_error_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_predicted_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_nobs_diffuse PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_scaled_smoothed_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothing_error SKIPPED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_forecasts_error_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_state_disturbance_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_predicted_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothing_error SKIPPED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_kalman_gain PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_state_disturbance PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_initialization_approx PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_loglike PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_filtered_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_nobs_diffuse PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_simulation_smoothed_state XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_state_autocov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_forecasts_error PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_scaled_smoothed_estimator PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_predicted_diffuse_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_scaled_smoothed_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_filtered_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_predicted_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_forecasts PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_forecasts_error_diffuse_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_initialization PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_measurement_disturbance PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLinearTrendAnalytic::test_results PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLinearTrendAnalyticMissing::test_results PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_forecasts PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_simulation_smoothed_state XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_nobs_diffuse PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_forecasts_error_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_scaled_smoothed_diffuse_estimator PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_filtered_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_scaled_smoothed_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_forecasts_error PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_kalman_gain PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_initialization PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_loglike PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_simulation_smoothed_state_disturbance XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_state_autocov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_state_disturbance PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_state_disturbance_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_forecasts_error_diffuse_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_predicted_diffuse_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_scaled_smoothed_estimator PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_measurement_disturbance_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_simulation_smoothed_measurement_disturbance XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_predicted_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothing_error SKIPPED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_predicted_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_filtered_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_measurement_disturbance PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_state_autocov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_simulation_smoothed_state XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_state_disturbance PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_predicted_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothing_error SKIPPED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_filtered_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_forecasts PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_predicted_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_nobs_diffuse PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_measurement_disturbance_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_scaled_smoothed_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_forecasts_error_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_loglike PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_measurement_disturbance PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_kalman_gain PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_state_disturbance_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_simulation_smoothed_measurement_disturbance XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_forecasts_error_diffuse_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_predicted_diffuse_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_initialization PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_filtered_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_forecasts_error PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_scaled_smoothed_estimator PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_scaled_smoothed_diffuse_estimator PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_simulation_smoothed_state_disturbance XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_predicted_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_kalman_gain PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_forecasts_error_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_state_disturbance_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_state_disturbance PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_scaled_smoothed_estimator PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothing_error SKIPPED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_initialization_approx PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_forecasts_error PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_nobs_diffuse PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_measurement_disturbance PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_forecasts_error_diffuse_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_forecasts PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_scaled_smoothed_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_initialization PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_simulation_smoothed_state XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_predicted_diffuse_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_loglike PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_filtered_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_predicted_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_filtered_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_state_autocov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_scaled_smoothed_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_forecasts_error_diffuse_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_kalman_gain PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_simulation_smoothed_state XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_state_disturbance PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_predicted_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_predicted_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_scaled_smoothed_diffuse_estimator PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_simulation_smoothed_state_disturbance XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_predicted_diffuse_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothing_error SKIPPED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_state_disturbance_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_state_autocov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_simulation_smoothed_measurement_disturbance XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_forecasts_error_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_initialization PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_forecasts PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_filtered_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_nobs_diffuse PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_measurement_disturbance PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_measurement_disturbance_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_forecasts_error PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_scaled_smoothed_estimator PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_filtered_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_loglike PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_scaled_smoothed_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_filtered_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_forecasts_error_diffuse_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_measurement_disturbance PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_state_disturbance PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_scaled_smoothed_diffuse_estimator PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_simulation_smoothed_state XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_initialization PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_predicted_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_predicted_state PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_state_disturbance_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_predicted_diffuse_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothing_error SKIPPED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_kalman_gain PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_loglike PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_forecasts PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_forecasts_error_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_state_autocov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_measurement_disturbance_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_filtered_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_scaled_smoothed_estimator PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_state_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_nobs_diffuse PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_forecasts_error PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_simulation_smoothed_measurement_disturbance XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_simulation_smoothed_state_disturbance XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::test_common_level_analytic PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::test_common_level_restricted_analytic PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::test_nondiagonal_obs_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::test_irrelevant_state XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLevelAnalyticDirect::test_results PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_scaled_smoothed_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_nobs_diffuse PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_state_autocov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_initialization_approx PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_scaled_smoothed_estimator PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_loglike PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_forecasts_error_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_kalman_gain PASSED [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 6%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_predicted_state PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothing_error SKIPPED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_filtered_state_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_predicted_state_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_forecasts_error_diffuse_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_state_disturbance PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_state_disturbance_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_simulation_smoothed_state XFAIL [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_forecasts_error PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_predicted_diffuse_state_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_filtered_state PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_forecasts PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_initialization PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_state_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_measurement_disturbance PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_state PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLinearTrendAnalyticDirect::test_results PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_measurement_disturbance PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_forecasts_error_diffuse_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_state_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_simulation_smoothed_measurement_disturbance XFAIL [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_kalman_gain PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_filtered_state PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_loglike PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_simulation_smoothed_state XFAIL [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_predicted_state PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_nobs_diffuse PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_state PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_scaled_smoothed_diffuse_estimator PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_filtered_state_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothing_error SKIPPED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_measurement_disturbance_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_predicted_diffuse_state_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_predicted_state_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_initialization PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_scaled_smoothed_estimator_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_state_autocov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_forecasts_error_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_forecasts PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_scaled_smoothed_estimator PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_state_disturbance_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_simulation_smoothed_state_disturbance XFAIL [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_forecasts_error PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_state_disturbance PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltHeuristicInitialization::test_heuristic PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltConcentratedInitialization::test_given_params PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltConcentratedInitialization::test_estimated_params PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedHeuristicInitialization::test_heuristic PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESKnownInitialization::test_given_params PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESKnownInitialization::test_estimated_params PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_misc PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_conf_int PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_output PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_fitted PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_states PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_forecasts PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_initial_states PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedKnownInitialization::test_estimated_params PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedKnownInitialization::test_given_params PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_states PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_fitted PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_misc PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_forecasts PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_mle_estimates PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_initial_states PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_conf_int PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_output PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendKnownInitialization::test_estimated_params PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendKnownInitialization::test_given_params PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_initial_states PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_forecasts PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_misc PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_states PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_fitted PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_conf_int PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_output PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_initial_states PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_states PASSED [ 7%] statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_conf_int 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That only cancels to zero when scale is the identity; here scale=diag(1/std_sigma), so the result is mean/std_sigma - mean, not zero. normalized() (a separate, non-affine implementation) gets this right by directly setting mean_new = zeros. The same shift-vs-scale bug affects .standardized(), see test_standardized_mean_is_zero below.) [ 7%] statsmodels/sandbox/distributions/tests/test_mv_normal.py::TestMVNormal::test_pdf_is_exp_logpdf PASSED [ 7%] statsmodels/sandbox/distributions/tests/test_mv_normal.py::TestMVNormal::test_whiten_standardize_relationship PASSED [ 7%] statsmodels/sandbox/distributions/tests/test_mv_normal.py::TestMVNormal::test_normalized_has_correlation_as_sigma_and_zero_mean PASSED [ 7%] statsmodels/sandbox/distributions/tests/test_mv_normal.py::TestMVNormal::test_cov_property_equals_sigma PASSED [ 7%] statsmodels/sandbox/distributions/tests/test_mv_normal.py::TestMVNormal::test_cdf_matches_scipy SKIPPEDmvstdnormcdf -> mvndst, a compiled scipy.stats Fortran routine that was removed in SciPy >= 1.16.0 (see sandbox.distributions.tests.test_multivariate for the same issue against mvstdtprob/mvstdnormcdf directly).) 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statsmodels/stats/tests/test_power.py::TestFtestPower::test_positional PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestFtestPower::test_roots PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestFtestPower::test_power_plot SKIPPED [ 8%] statsmodels/stats/tests/test_power.py::TestFtestPower::test_kwargs PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerOneS4::test_power_plot PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerOneS4::test_positional PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerOneS4::test_roots PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerOneS4::test_power PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestNormalIndPower2::test_roots PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestNormalIndPower2::test_power PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestNormalIndPower2::test_positional PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestNormalIndPower2::test_power_plot PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerTwoS4::test_power PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerTwoS4::test_roots PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerTwoS4::test_power_plot PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerTwoS4::test_positional PASSED [ 8%] statsmodels/stats/tests/test_power.py::test_normal_power_explicit PASSED [ 8%] statsmodels/stats/tests/test_power.py::test_ftest_power PASSED [ 8%] statsmodels/stats/tests/test_power.py::test_alternative_deprecated_alias[normal_power_het] PASSED [ 8%] statsmodels/stats/tests/test_power.py::test_alternative_deprecated_alias[ttest_power] PASSED [ 8%] statsmodels/stats/tests/test_power.py::test_normal_sample_size_one_tail PASSED [ 8%] statsmodels/stats/tests/test_power.py::test_alternative_deprecated_alias[normal_power] PASSED [ 8%] statsmodels/stats/tests/test_power.py::test_solve_power_no_solution_returns_nan PASSED [ 8%] statsmodels/stats/tests/test_power.py::test_power_solver_warn XFAIL [ 8%] statsmodels/stats/tests/test_power.py::test_power_solver PASSED [ 8%] statsmodels/stats/tests/test_power.py::test_solve_power_impossible_one_sided_raises PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerTwoS5::test_positional PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerTwoS5::test_power_plot PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerTwoS5::test_roots PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerTwoS5::test_power PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerTwoS1::test_power PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerTwoS1::test_positional PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerTwoS1::test_power_plot PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerTwoS1::test_roots PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerOneS1::test_roots PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerOneS1::test_power PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerOneS1::test_positional PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerOneS1::test_power_plot PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerOneS5::test_power PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerOneS5::test_roots PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerOneS5::test_positional PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestTTPowerOneS5::test_power_plot PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestNormalIndPower_onesamp2::test_roots PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestNormalIndPower_onesamp2::test_power PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestNormalIndPower_onesamp2::test_power_plot PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestNormalIndPower_onesamp2::test_positional PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestChisquarePower::test_power PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestChisquarePower::test_roots PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestChisquarePower::test_power_plot PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestChisquarePower::test_positional PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestFtestAnovaPower::test_positional PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestFtestAnovaPower::test_power PASSED [ 8%] statsmodels/stats/tests/test_power.py::TestFtestAnovaPower::test_roots PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::TestHoltWinters::test_forecast XFAIL [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::TestHoltWinters::test_forecast XFAIL [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::TestHoltWinters::test_hw_seasonal_add_mul PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::TestHoltWinters::test_hw_seasonal_buggy PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::TestHoltWinters::test_hw_seasonal PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::TestHoltWinters::test_holt_damp_r PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::TestHoltWinters::test_predict PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::TestHoltWinters::test_simple_exp_smoothing PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::TestHoltWinters::test_holt PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::TestHoltWinters::test_holt_damp_fit PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::TestHoltWinters::test_ndarray PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-False-None-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_alternative_minimizers[basinhopping] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-False-None-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-True-None-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_alternative_minimizers[L-BFGS-B] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_start_params[None-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-True-mul-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_estimated_initialization_short_data[10-add-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_float_boxcox[add-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_initialization_methods[None-add-heuristic] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-True-add-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-True-mul-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_equivalence_cython_python[add-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_alternative_minimizers[trust-constr] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-True-None-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_initialization_methods[None-None-legacy-heuristic] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_brute[add-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_forecast_index_types[range] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_float_boxcox[add-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_2d_data PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_estimated_initialization_short_data[10-None-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_initialization_methods[add-add-legacy-heuristic] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-False-None-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_start_params[add-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-False-add-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_fixed_errors PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_estimated_initialization_short_data[10-add-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_all_initial_values PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_initialization_methods[add-add-heuristic] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-False-mul-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_estimated_initialization_short_data[9-add-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_fix_set_parameters PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_equivalence_cython_python[add-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-False-mul-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_keywords PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_basin_hopping PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_forecast_index[10] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_forecast_index[100] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_float_boxcox[mul-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-False-add-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_initialization_methods[None-add-estimated] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-False-add-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_boxcox PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_float_boxcox[None-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_forecast_index_types[date_range] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_valid_bounds PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_start_params[mul-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-False-mul-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_alternative_minimizers[SLSQP] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_equivalence_cython_python[mul-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_fix_unfixable PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_invalid_seasonal[mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_estimated_initialization_short_data[9-None-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_equivalence_cython_python[None-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_error_boxcox PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_equivalence_cython_python[mul-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_estimated_initialization_short_data[10-None-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_equivalence_cython_python[None-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_alternative_minimizers[Powell] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_dampen_no_trend[add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_initialization_methods[add-add-estimated] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_infeasible_bounds PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-True-add-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_brute[None-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_error_aliases PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-True-mul-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_float_boxcox[mul-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_integer_array PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-True-None-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-True-add-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-False-None-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_error_dampen PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_use_boxcox_fit_override PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-True-None-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_initialization_methods[add-None-estimated] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_equivalence_cython_python[add-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_brute[add-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_direct_holt_add PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_summary_boxcox PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-True-mul-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-True-mul-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-False-add-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_alternative_minimizers[TNC] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_negative_multipliative[trend_seasonal1] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_start_params[mul-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_float_boxcox[add-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_no_params_to_optimize PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_negative_multipliative[trend_seasonal0] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-True-mul-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_start_params[None-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_initialization_methods[None-None-heuristic] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_initial_level PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_damping_trend_zero PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_float_boxcox[None-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_fixed_basic PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_estimated_initialization_short_data[9-add-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_negative_multipliative[trend_seasonal2] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_estimated_initialization_short_data[9-None-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_invalid_start_param_length PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-False-mul-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_dampen_no_trend[None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_bad_bounds PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-False-add-add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_start_params[add-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-False-None-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_forecast_index[1000] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_error_initialization PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_brute[None-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_equivalence_cython_python[None-mul] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_to_restricted_equiv[params1] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_initialization_methods[add-None-heuristic] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_invalid_seasonal[add] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_restricted_round_tip[params2] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-True-None-None] PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_different_inputs PASSED [ 8%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_boxcox_components PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_alternative_minimizers[least_squares] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-False-mul-add] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_start_params[mul-mul] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_forecast_1_simulation[bootstrap-10] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_initialization_methods[add-None-legacy-heuristic] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_float_boxcox[None-mul] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_forecast_index_types[period] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-False-add-mul] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_debiased PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_invalid_index PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_to_restricted_equiv[params0] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_initialization_methods[None-None-estimated] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_infer_freq PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-False-None-add] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-True-add-add] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-True-None-mul] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_forecast_1_simulation[None-1] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_float_boxcox[mul-add] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[add-False-mul-None] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_to_restricted_equiv[params2] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_initialization_methods[None-add-legacy-heuristic] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_restricted_round_tip[params1] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-True-add-None] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate_expected_r[mul-True-add-add] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_attributes PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_minimizer_kwargs_error PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_start_params[add-None] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_restricted_round_tip[params0] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_dampen_no_trend[mul] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_forecast_index[2000] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_forecast_1_simulation[bootstrap-1] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_forecast_1_simulation[None-10] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_simulate PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_start_params[None-None] PASSED [ 9%] statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_equivalence_cython_python[mul-add] PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2s::test_plot_simultaneous_ci PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2s::test_shortcut_function PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2s::test_multicomptukey PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2s::test_group_tukey PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2Pandas::test_table_names_custom_group_order PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2Pandas::test_group_tukey PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2Pandas::test_incorrect_output PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2Pandas::test_shortcut_function PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2Pandas::test_multicomptukey PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2Pandas::test_table_names_default_group_order PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2Pandas::test_plot_simultaneous_ci PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD4::test_shortcut_function PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD4::test_group_tukey PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD4::test_hochberg_intervals PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD4::test_plot_simultaneous_ci PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD4::test_multicomptukey PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTukeyHSD2sUnequal::test_multicomptukey PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTukeyHSD2sUnequal::test_group_tukey PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTukeyHSD2sUnequal::test_plot_simultaneous_ci PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTukeyHSD2sUnequal::test_shortcut_function PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2::test_table_names_custom_group_order PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2::test_shortcut_function PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2::test_plot_simultaneous_ci PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2::test_group_tukey PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2::test_multicomptukey PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD2::test_table_names_default_group_order PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::test_tukeyhsd_invalid_use_var_raises PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::test_plot PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD3::test_group_tukey PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD3::test_plot_simultaneous_ci PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD3::test_multicomptukey PASSED [ 9%] statsmodels/stats/tests/test_pairwise.py::TestTuckeyHSD3::test_shortcut_function PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_zstat PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_k PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_endog_names PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_normalized_cov_params XFAIL [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_margeff_mean PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_distr XFAIL [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_llr_pvalue PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_predict_xb PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_jac PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_loglikeobs PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_j PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_resid PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_margeff_overall PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_dof PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_pvalues PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_cov_params XFAIL [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_bic PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_aic PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_pred_table PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_llf PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_llr PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_params PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_summary_latex PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_margeff_dummy PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_llnull PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_conf_int PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_fit_regularized_invalid_method PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_predict PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_bse PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_llf PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_aic PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_bic PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_df PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_bse PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_alpha PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_conf_int PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_params PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_t PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_wald PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_distr PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_jac PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_params PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_resid_generalized PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_llnull PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_pvalues PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_jac PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_resid_response PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_pred_table PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_cov_params PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_fit_regularized_invalid_method PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_predict PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_loglikeobs PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_conf_int PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_predict_xb PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_bse PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_summary_latex PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_llr_pvalue PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_resid_dev PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_dof PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_zstat PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_normalized_cov_params XFAIL [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_distr PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_bic PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_aic PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_llf PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_llr PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dydxoverall PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_predict PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dyexoverall PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_loglikeobs PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_dydxmean PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_predict_xb PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_llnull PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_summary_latex PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_params PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_exog1 PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_resid_dev PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_bse PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dof PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_llr_pvalue PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eyexmedian PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_fit_regularized_invalid_method PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_aic PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_exog2 PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dyexmean PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_bic PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_llf PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eydxmean PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_dydxoverall PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dydxmedian PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_pvalues PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dydxzero PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eyexzero PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_llr PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eydxmedian PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_normalized_cov_params XFAIL [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_count_dummy_dydxmean PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_count_dydxmean PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_exog2 PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_resid_pearson PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dyexmedian PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_jac PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dydxmean PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_eydxoverall PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eyexmean PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_conf_int PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dyexzero PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eydxzero PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_count_dummy_dydxoverall PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_distr PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_diagnostic PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eydxoverall PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_resid_response PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eyexoverall PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_eydxmean PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_pred_table PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_cov_params PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_count_dydxoverall PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_resid_generalized PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_exog1 PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_zstat PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_alpha PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_bse PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_llf PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_aic PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_bic PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_df PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_conf_int PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_params PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_predict PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_dof PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_llr PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_cov_params SKIPPED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_llf PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_bic PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_aic PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_zstat PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_fit_regularized_invalid_method PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_bse PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_params PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_pvalues XFAIL [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_distr PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_llnull PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_conf_int PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_summary_latex PASSED [ 9%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_llr_pvalue PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_normalized_cov_params XFAIL [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_loglikeobs PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_fittedvalues PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_predict_xb PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_alpha PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_jac PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeoL1Compatability::test_f_test PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeoL1Compatability::test_df PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeoL1Compatability::test_t_test PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeoL1Compatability::test_bad_r_matrix PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeoL1Compatability::test_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeoL1Compatability::test_cov_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_predict_xb PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_llnull PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_conf_int PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_bse PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_margeff_mean PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_loglikeobs PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_endog_names PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_dof PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_fit_regularized_invalid_method PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_resid PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_llr_pvalue PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_llr PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_llf PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_aic PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_bic PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_pvalues PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_k PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_jac PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_margeff_overall PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_cov_params XFAIL [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_distr XFAIL [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_normalized_cov_params XFAIL [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_j PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_predict PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_margeff_dummy PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_summary_latex PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_zstat PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_pred_table PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_resid_generalized PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_resid_response PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_pvalues PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_conf_int PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_dof PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_zstat PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_llr PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_distr PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_bic PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_aic PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_llf PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_cov_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_resid_dev PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_fit_regularized_invalid_method PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_normalized_cov_params XFAIL [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_bse PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_pred_table PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_llnull PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_predict PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_predict_xb PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_loglikeobs PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_llr_pvalue PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_summary_latex PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_jac PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_llr PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_predict PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_loglikeobs PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_bic PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_aic PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_llf PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_predict_xb PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_resid_response PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_dof PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_bse PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_llr_pvalue PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_conf_int PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_llnull PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_resid_dev PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_pvalues PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_normalized_cov_params XFAIL [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_summary_latex PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_fit_regularized_invalid_method PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_zstat PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_pred_table PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_jac PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_cov_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_distr PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_resid_generalized PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitL1::test_cov_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitL1::test_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitL1::test_aic PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitL1::test_bic PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitL1::test_conf_int PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitL1::test_nnz_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitL1::test_bse PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNBP2Null::test_start_null PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNBP2Null::test_llnull PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eydxoverall PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_exog2 PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_resid_pearson PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eyexoverall PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dyexzero PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eydxzero PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dydxmean PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eyexmean PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_count_dummy_dydxmean PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_dydxoverall PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_dydxmean PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dyexmedian PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_exog1 PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eydxmedian PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_eydxoverall PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_eydxmean PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_count_dummy_dydxoverall PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_exog1 PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dydxmedian PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eyexmedian PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_exog2 PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_count_dydxoverall PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dydxoverall PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_count_dydxmean PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dyexoverall PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dydxzero PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eyexzero PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dyexmean PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eydxmean PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_distr PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_predict_xb PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_loglikeobs PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_predict PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_zstat PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_init_kwds PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_conf_int PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_lnalpha PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_pvalues XFAIL [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_jac PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_llr_pvalue PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_dof PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_llnull PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_summary_latex PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_aic PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_bic PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_fit_regularized_invalid_method PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_llf PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_llr PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_cov_params SKIPPED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_normalized_cov_params XFAIL [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_bse PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialL1Compatability::test_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialL1Compatability::test_bad_r_matrix PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialL1Compatability::test_cov_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialL1Compatability::test_df PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialL1Compatability::test_f_test PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialL1Compatability::test_t_test PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_zstat PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_dof PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_cov_params SKIPPED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_llf PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_bic PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_aic PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_llr PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_distr PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_summary_latex PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_fit_regularized_invalid_method PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_bse PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_llnull PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_llr_pvalue PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_predict XFAIL [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_lnalpha PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_pvalues XFAIL [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_predict_xb XFAIL [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_conf_int PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_loglikeobs PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_normalized_cov_params XFAIL [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_jac PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_basic PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_jac PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_predict_prob PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_newton PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_mean_var PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_distr PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_f_test PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_t_test PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_bad_r_matrix PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_cov_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_df PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_llnull PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_resid_generalized PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_cov_params PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_summary_latex PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_pred_table PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_pvalues PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_fit_regularized_invalid_method PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_jac PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_zstat PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_conf_int PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_predict PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_distr PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_resid_dev PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_bic PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_aic PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_normalized_cov_params XFAIL [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_llf PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_llr PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_dof PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_llr_pvalue PASSED [ 10%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_predict_xb PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_bse PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_loglikeobs PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_resid_response PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNBP1Null::test_start_null PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNBP1Null::test_llnull PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitL1Compatability::test_params PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitL1Compatability::test_df PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitL1Compatability::test_f_test PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitL1Compatability::test_t_test PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitL1Compatability::test_cov_params PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitL1Compatability::test_bad_r_matrix PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_loglikeobs PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_predict_xb PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_llr_pvalue PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_distr PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_zstat PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_llnull PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_params PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_jac PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_predict PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_dof PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_fit_regularized_invalid_method PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_normalized_cov_params XFAIL [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_llr PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_summary_latex PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_aic PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_bic PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_llf PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_alpha PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_fittedvalues PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_cov_params SKIPPED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_bse PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_pvalues XFAIL [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_conf_int PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestCVXOPT::test_cvxopt_versus_slsqp SKIPPED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_dof PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_llr_pvalue PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_conf_int PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_summary_latex PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_llf PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_bic PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_pvalues PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_aic PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_resid PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_llr PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_normalized_cov_params XFAIL [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_margeff_overall PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_predict PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_loglikeobs PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_predict_xb PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_predict_prob PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_bse PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_distr PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_zstat PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_cov_params XFAIL [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_fit_regularized_invalid_method PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_params PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_margeff_dummy_overall PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_llnull PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_jac PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_predict PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_predict_xb PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_loglikeobs PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_zstat PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_jac PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_conf_int PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_summary_latex PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_params PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_llr_pvalue PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_lnalpha PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_llnull PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_distr PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_pvalues XFAIL [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_llr PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_llf PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_bic PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_aic PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_dof PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_bse PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_cov_params SKIPPED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_fit_regularized_invalid_method PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_normalized_cov_params XFAIL [ 11%] statsmodels/discrete/tests/test_discrete.py::TestL1AlphaZeroLogit::test_tests PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestL1AlphaZeroLogit::test_converged PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestL1AlphaZeroLogit::test_basic_results PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitScoreTest::test_score_factor_consistency PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitScoreTest::test_score_test_smoke PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitScoreTest::test_score_test_4_categories PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitScoreTest::test_score_wald_equivalence PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitScoreTest::test_score_test_hc0 PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitScoreTest::test_score_test_df PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitScoreTest::test_hessian_factor_consistency PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_resid_generalized PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_distr PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_llr_pvalue PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_resid_dev PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_zstat PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_jac PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_loglikeobs PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_params PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_llnull PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_predict_xb PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_pred_table PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_summary_latex PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_init_kwargs PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_conf_int PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_predict PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_bse PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_cov_params PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_normalized_cov_params XFAIL [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_dof PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_fit_regularized_invalid_method PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_llr PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_pvalues PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_resid_response PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_llf PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_aic PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_bic PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_predict_xb XFAIL [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_normalized_cov_params XFAIL [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_loglikeobs PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_jac PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_fit_regularized_invalid_method PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_summary_latex PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_llr_pvalue PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_dof PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_pvalues XFAIL [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_conf_int PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_lnalpha PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_aic PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_bic PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_llf PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_llr PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_zstat PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_cov_params SKIPPED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_predict XFAIL [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_params PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_distr PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_llnull PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_bse PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_loglikeobs PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_predict PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_bse PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_conf_int PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_predict_xb PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_resid_response PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_llr_pvalue PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_dof PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_pvalues PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_llr PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_bic PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_aic PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_llf PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_resid_generalized PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_normalized_cov_params XFAIL [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_jac PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_distr PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_pred_table PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_resid_dev PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_summary_latex PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_llnull PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_fit_regularized_invalid_method PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_cov_params PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_zstat PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_params PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestLogitL1Compatability::test_params PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestLogitL1Compatability::test_bad_r_matrix PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestLogitL1Compatability::test_df PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestLogitL1Compatability::test_t_test PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestLogitL1Compatability::test_cov_params PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestLogitL1Compatability::test_f_test PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_score PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_hessian PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_init_kwds PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_distr PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_llf PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_t PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_fit_regularized PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_fit_regularized_invalid_method PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_cov_params SKIPPED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_jac PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_pvalues XFAIL [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_predict PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_fittedvalues PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_bse PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_distr PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_zstat PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_conf_int PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_summary_latex PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_llr_pvalue PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_llr PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_normalized_cov_params XFAIL [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_predict_xb PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_bic PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_aic PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_llf PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_llnull PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_dof PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_loglikeobs PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_params PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestL1AlphaZeroMNLogit::test_basic_results PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_jac PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_llr_pvalue PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_predict PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_loglikeobs PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_pvalues PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_predict_xb PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_pred_table PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_summary_latex PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_bse PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_conf_int PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_cov_params PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_resid_response PASSED [ 11%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_resid_generalized PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_distr PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_resid_dev PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_llr PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_llf PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_bic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_aic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_llnull PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_fit_regularized_invalid_method PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_normalized_cov_params XFAIL [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_dof PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_zstat PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_mnlogit_factor PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_formula_missing_exposure PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_poisson_predict PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_issue_341 PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_issue_8943 PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_l1_regularized_respects_warning_filters PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_isdummy PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_poisson_newton PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_perfect_prediction PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_mnlogit_factor_categorical PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_issue_339 PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_iscount PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_mnlogit_basinhopping PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_negative_binomial_default_alpha_param PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_binary_pred_table_zeros PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_non_binary PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_predict_with_exposure PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_im_ratio_nonrobust_and_robust PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_cov_confint_pandas PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_summary_after_remove_data[NegativeBinomial] PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_summary_after_remove_data[Probit] PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_logit_family_is_binomial PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_generalized_poisson_score_p_var_prob_nonzero PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_summary_after_remove_data[MNLogit] PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_summary_after_remove_data[NegativeBinomialP] PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_mlogit_t_test PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_summary_after_remove_data[Poisson] PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_null_options PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_binary_results_info_criteria PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_summary_after_remove_data[Logit] PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_summary_after_remove_data[GeneralizedPoisson] PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_poisson_cdf_pdf_match_scipy PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_count_model_fit_regularized_direct PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_mnlogit_float_name PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_cov_params_func_l1_raises_on_nonfinite_hessian PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_unchanging_degrees_of_freedom PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_mnlogit_resid_response PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::test_optim_kwds_prelim PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_jac PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_pvalues XFAIL [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_llr_pvalue PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_alpha PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_predict_xb PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_normalized_cov_params XFAIL [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_loglikeobs PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_conf_int PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_predict PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_fittedvalues PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_cov_params SKIPPED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_bse PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_fit_regularized_invalid_method PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_llf PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_aic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_bic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_summary_latex PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_llnull PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_llr PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_distr PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_dof PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_zstat PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Null::test_llnull PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_pvalues PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_loglikeobs PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_llnull PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_jac PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_conf_int PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_predict_xb PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_zstat PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_llr_pvalue PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_resid_dev PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_resid_response PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_predict PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_distr PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_bse PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_dof PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_pred_table PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_aic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_bic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_llf PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_fit_regularized_invalid_method PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_normalized_cov_params XFAIL [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_resid_generalized PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_cov_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_summary_latex PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_llr PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_fit_regularized_invalid_method PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_llr_pvalue PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_jac PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_predict_xb PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_distr PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_llnull PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_loglikeobs PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_zstat PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_cov_params SKIPPED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_normalized_cov_params XFAIL [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_predict PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_conf_int PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_bse PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_summary_latex PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_dof PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_alpha PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_fittedvalues PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_pvalues XFAIL [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_llr PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_bic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_aic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_llf PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestPoissonNull::test_llnull PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestSweepAlphaL1::test_sweep_alpha PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitL1::test_cov_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitL1::test_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitL1::test_conf_int PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitL1::test_bse PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitL1::test_nnz_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitL1::test_aic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitL1::test_bic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1::test_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1::test_bse PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1::test_conf_int PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1::test_aic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1::test_bic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1::test_nnz_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_dof PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_resid_response PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_distr PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_predict PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_bic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_zstat PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_fit_regularized_invalid_method PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_aic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_llf PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_llr_pvalue PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_llr PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_predict_xb PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_resid_dev PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_loglikeobs PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_summary_latex PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_pvalues PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_bse PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_llnull PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_cov_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_conf_int PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_pred_table PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_resid_generalized PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_normalized_cov_params XFAIL [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_jac PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestL1AlphaZeroProbit::test_basic_results PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestL1AlphaZeroProbit::test_tests PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_predict_xb PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_predict PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_loglikeobs PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_fit_regularized_invalid_method PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_llnull PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_jac PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_resid_response PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_pvalues PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_llr_pvalue PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_normalized_cov_params XFAIL [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_llr PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_llf PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_aic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_bic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_resid_dev PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_dof PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_zstat PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_bse PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_summary_latex PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_resid_generalized PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_cov_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_conf_int PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_pred_table PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_distr PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoissonNull::test_llnull PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPPredictProb::test_predict_prob_p2 PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPPredictProb::test_predict_prob_p1 PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_fit_regularized_invalid_method PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_llf PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_aic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_conf_int PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_bic PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_pred_table PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_llr PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_count_dydxmean PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dydxmean PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eyexmean PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_llnull PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_dof PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_dummy_eydxoverall PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dyexzero PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eydxzero PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_cov_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_params PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_resid_response PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dyexmedian PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_count_dummy_dydxoverall PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_dummy_eydxmean PASSED [ 12%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_bse PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_count_dummy_dydxmean PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dyexoverall PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_resid_generalized PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eydxmedian PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_count_dydxoverall PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dydxoverall PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dydxmedian PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_normalized_cov_params XFAIL [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_dummy_dydxmean PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_predict PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_llr_pvalue PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eyexmedian PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eyexoverall PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eydxoverall PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_jac PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_loglikeobs PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_zstat PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_resid_dev PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_summary_latex PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_pvalues PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dyexmean PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eydxmean PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_dummy_dydxoverall PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_predict_xb PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dydxzero PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_distr PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eyexzero PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Null::test_llnull PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestPoissonL1Compatability::test_bad_r_matrix PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestPoissonL1Compatability::test_cov_params PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestPoissonL1Compatability::test_params PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestPoissonL1Compatability::test_t_test PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestPoissonL1Compatability::test_df PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestPoissonL1Compatability::test_f_test PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1Compatability::test_params PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1Compatability::test_t_test PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1Compatability::test_bad_r_matrix PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1Compatability::test_f_test SKIPPED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1Compatability::test_cov_params PASSED [ 13%] statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1Compatability::test_df PASSED [ 13%] statsmodels/tools/tests/test_sequences.py::test_primes_array PASSED [ 13%] statsmodels/tools/tests/test_sequences.py::test_primes PASSED [ 13%] statsmodels/tools/tests/test_sequences.py::test_halton PASSED [ 13%] statsmodels/tools/tests/test_sequences.py::test_van_der_corput PASSED [ 13%] statsmodels/tools/tests/test_sequences.py::test_discrepancy PASSED [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_arcovariance_fit_with_explicit_method PASSED [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_whiten_ar_matches_manual_ar1_transform PASSED [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_yule_walker_acov_with_valid_method PASSED [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_whiten_ar_order_zero_is_identity PASSED [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_whiten_ar_2d PASSED [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_corr_ar_truncates_long_ar XFAILars; when `ar` is already >= k_vars long it is passed to toeplitz() unmodified/untruncated, so the returned matrix has shape (len(ar), len(ar)) instead of the documented (k_vars, k_vars).) [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_corr2cov_scalar_std PASSED [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_arcovariance_corr_from_ar_coefs PASSED [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_corr_equi PASSED [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_corr_arma PASSED [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_yule_walker_acov_default_method_is_broken PASSED [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_arcovariance_cov XFAILs it as self.sigma, so .cov() always raises AttributeError. Separately, .cov() calls cov2corr(self.corr(...), self.sigma) -- cov2corr converts covariance to correlation, the opposite of what a method named .cov() should be doing; it likely meant to call this module's own corr2cov(corr, std) instead.) [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_corr2cov_roundtrip_with_cov2corr PASSED [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_arcovariance_fit_default_method XFAILs) without a method= kwarg, hitting the same broken default as test_yule_walker_acov_default_method_is_broken, so .fit() always raises unless the caller passes method= explicitly.) [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_arcovariance_whiten_after_ar_coefs_construction XFAILs (no underscore), but .whiten() reads self.ar_coefs (with underscore) -- a typo that means .whiten() always raises AttributeError when the instance was built via the ar_coefs= constructor path.) [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_arcovariance_corr_from_ar PASSED [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_arcovariance_ar_and_ar_coefs_constructions_are_equivalent PASSED [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_arcovariance_whiten_after_ar_construction XFAILar= or ar_coefs=) ever sets self.order, so .whiten() always raises AttributeError regardless of how the instance was built.) [ 13%] statsmodels/sandbox/panel/tests/test_correlation_structures.py::test_corr_ar_pads_short_ar PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_ar6_no_quarterly PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[MS-Q-JAN] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_standardized_MQ[False] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_em_invalid_mstep_method PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_simulate_standardized_1d[standardize2-True] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_news_MQ PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_simulate_standardized_1d[standardize1-False] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_standardized_monthly[False-2-True] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_simulate_standardized_2d[standardize1-False] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_idiosyncratic_ar1_False PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_simulate_standardized_1d[standardize1-True] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_standardized_monthly[True-1-False] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_standardized_monthly[False-1-True] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_coefficient_of_determination PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_summary_after_remove_data PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_invalid_model_specification PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_standardized_monthly[False-1-False] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_news_monthly PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_append_extend_apply PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_k_factors_gt1 PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[M-QS] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_standardized_monthly[True-1-True] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_simulate_standardized_1d[standardize3-False] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_simulate_standardized_2d[standardize1-True] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[MS-Q-DEC] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_simulate_standardized_2d[standardize2-True] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_k_factors_gt1_factor_order_gt1 PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_factor_order_gt1 PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_standardized_monthly[True-2-True] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[MS-QS] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_simulate_standardized_1d[standardize0-True] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[M-QS-DEC] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_simulate_standardized_1d[standardize2-False] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_standardized_monthly[True-2-False] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[MS-Q] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_simulate_standardized_2d[standardize2-False] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_simulate_standardized_1d[standardize3-True] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_standardized_monthly[False-2-False] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[MS-QS-DEC] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[M-Q-DEC] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_summary PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[MS-QS-APR] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_filter_reproduces_model_loglike PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_standardized_MQ[True] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_simulate_standardized_1d[standardize0-False] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[M-Q] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_factor_order_12 PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[M-Q-JAN] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_default PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_invalid_standardize_1d PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_simulate_standardized_2d[standardize0-False] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_simulate_standardized_2d[standardize0-True] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_results_factors PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_k_factors_gt1_factor_order_gt1_no_idiosyncratic_ar1 PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[M-QS-APR] PASSED [ 13%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py::test_quasi_newton_fitting PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_degrees PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_pvalues PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_sumof_squaredresids PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_confidenceintervals PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_norm_resids PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_wresid PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_bic PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_aic PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_params PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_mse_resid PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_scale PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_loglike PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_mse_model PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_fvalue PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_mse_total PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_rsquared_adj PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_resids PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_standarderrors PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_rsquared PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestRTO::test_ess PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_resids PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_loglike PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_rsquared PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_scale PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_ess PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_pvalues PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_degrees PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_sumof_squaredresids PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_aic PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_bic PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_confidenceintervals PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_params PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_mse_resid PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_norm_resids PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_wresid PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_mse_model PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_standarderrors PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_rsquared_adj PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_fvalue PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNx::test_mse_total PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_standarderrors PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_degrees PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_aic PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_bic PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_norm_resids PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_pvalues PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_resids PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_loglike PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_sumof_squaredresids PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_mse_resid PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_confidenceintervals PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_mse_model PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_scale PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_mse_total PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_rsquared PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_ess PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_fvalue PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_rsquared_adj PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_params PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestNxNxOne::test_wresid PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestTtest2::test_df_denom PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestTtest2::test_pvalue PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestTtest2::test_effect PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestTtest2::test_tvalue PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestTtest2::test_sd PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_rsquared_adj PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_fvalue PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_aic PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_bic PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_norm_resids PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_rsquared PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_wresid PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_params PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_sumof_squaredresids PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_degrees PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_confidenceintervals PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_resids PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_pvalues PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_scale PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_mse_model PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_mse_total PASSED [ 13%] statsmodels/regression/tests/test_regression.py::TestDataDimensions::test_loglike PASSED [ 13%] 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PASSED [ 14%] statsmodels/regression/tests/test_regression.py::TestNxOneNx::test_aic PASSED [ 14%] statsmodels/regression/tests/test_regression.py::TestNxOneNx::test_resids PASSED [ 14%] statsmodels/regression/tests/test_regression.py::TestNxOneNx::test_rsquared PASSED [ 14%] statsmodels/regression/tests/test_regression.py::TestTtest::test_effect PASSED [ 14%] statsmodels/regression/tests/test_regression.py::TestTtest::test_new_tvalue PASSED [ 14%] statsmodels/regression/tests/test_regression.py::TestTtest::test_tvalue PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestTtest::test_df_denom PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestTtest::test_sd PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestTtest::test_pvalue PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_mse_total PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_large_equal_params PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_degrees PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_mse_model PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_bic PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_aic PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_mse_resid PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_pvalues PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_large_equal_params_none PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_rsquared PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_wresid PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_params PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_loglike PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_standarderrors PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_fvalue PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_rsquared_adj PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_ess PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_scale PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_resids PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_sumof_squaredresids PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_confidenceintervals PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_norm_resids PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestGLS_large_data::test_large_equal_loglike PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_norm_resids PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_rsquared PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_loglike PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_aic PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_bic PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_resids PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_rsquared_adj PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_degrees PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_pvalues PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_sumof_squaredresids PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_confidenceintervals PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_mse_total PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_mse_model PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_ess PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_mse_resid PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_scale PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_standarderrors PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_fvalue PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_params PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_GLS::test_wresid PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestFtest::test_Df_num PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestFtest::test_Df_denom PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestFtest::test_p PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestFtest::test_F PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_rsquared PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_norm_resids PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_resids PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_bic PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_aic PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_standarderrors PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_scale PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_pvalues PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_mse_total PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_params PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_mse_model PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_wresid PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_fvalue PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_mse_resid PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_degrees PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_sumof_squaredresids PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_ess PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_confidenceintervals PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_loglike PASSED [ 15%] statsmodels/regression/tests/test_regression.py::TestWLS_OLS::test_rsquared_adj PASSED [ 15%] statsmodels/iolib/tests/test_summary2.py::TestSummaryLabels::test_absence_of_r2 PASSED [ 15%] statsmodels/iolib/tests/test_summary2.py::TestSummaryLabels::test_summary_col_r2 PASSED [ 15%] statsmodels/iolib/tests/test_summary2.py::test_ols_summary_rsquared_label PASSED [ 15%] statsmodels/iolib/tests/test_summary2.py::TestSummaryLatex::test_summary_col_ordering_preserved PASSED [ 15%] statsmodels/iolib/tests/test_summary2.py::TestSummaryLatex::test_summarycol_drop_omitted PASSED [ 15%] statsmodels/iolib/tests/test_summary2.py::TestSummaryLatex::test_summarycol_float_format PASSED [ 15%] statsmodels/iolib/tests/test_summary2.py::TestSummaryLatex::test_summarycol PASSED [ 15%] statsmodels/iolib/tests/test_summary2.py::TestSummaryLatex::test_summarycol_fixed_effects PASSED [ 15%] statsmodels/iolib/tests/test_summary2.py::TestSummaryLatex::test_OLSsummary PASSED [ 15%] statsmodels/iolib/tests/test_summary2.py::TestSummaryLatex::test__repr_latex_ PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[strikes] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[interest_inflation] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[elnino] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[cpunish] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[danish_data] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[ccard] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[committee] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[star98] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[grunfeld] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[cancer] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[longley] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[fair] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[randhie] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[fertility] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[nile] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[engel] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[statecrime] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[macrodata] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[scotland] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[spector] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[stackloss] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[copper] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[modechoice] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[china_smoking] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[anes96] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[co2] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[sunspots] PASSED [ 15%] statsmodels/datasets/tests/test_data.py::test_dataset[heart] PASSED [ 15%] statsmodels/iolib/tests/test_pickle.py::test_pickle PASSED [ 15%] statsmodels/iolib/tests/test_pickle.py::test_pickle_supports_open PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceBinomialGLMMLE::test_summary PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceBinomialGLMMLE::test_plots PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceBinomialGLMMLE::test_r PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceBinomialGLMMLE::test_looo PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceBinomialGLMMLE::test_basics PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluencePoissonCompare::test_basics PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluencePoissonCompare::test_plots PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluencePoissonCompare::test_summary PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceLogitGLMMLE::test_summary PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceLogitGLMMLE::test_plots PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceLogitGLMMLE::test_basics PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceLogitGLMMLE::test_looo PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceGaussianGLMOLS::test_basics PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceGaussianGLMOLS::test_summary PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceGaussianGLMOLS::test_plots PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceLogitCompare::test_plots PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceLogitCompare::test_summary PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceLogitCompare::test_basics PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceGaussianGLMMLE::test_basics PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceGaussianGLMMLE::test_plots PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceGaussianGLMMLE::test_summary PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceGaussianGLMMLE::test_looo PASSED [ 15%] statsmodels/stats/tests/test_influence.py::test_influence_glm_bernoulli PASSED [ 15%] statsmodels/stats/tests/test_influence.py::test_glminfluence_direct_constructor PASSED [ 15%] statsmodels/stats/tests/test_influence.py::test_olsinfluence_ols_xnoti_and_get_drop_vari PASSED [ 15%] statsmodels/stats/tests/test_influence.py::test_vif_instability PASSED [ 15%] statsmodels/stats/tests/test_influence.py::test_olsinfluence_closed_form_measures PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceProbitCompare::test_summary PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceProbitCompare::test_plots PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceProbitCompare::test_basics_specific PASSED [ 15%] statsmodels/stats/tests/test_influence.py::TestInfluenceProbitCompare::test_basics PASSED [ 15%] statsmodels/tsa/statespace/tests/test_chandrasekhar.py::test_chandrasekhar_univariate PASSED [ 15%] statsmodels/tsa/statespace/tests/test_chandrasekhar.py::test_chandrasekhar_conventional PASSED [ 15%] statsmodels/tsa/statespace/tests/test_chandrasekhar.py::test_invalid PASSED [ 15%] statsmodels/compat/tests/test_itercompat.py::test_zip_longest PASSED [ 15%] statsmodels/compat/tests/test_itercompat.py::test_combinations PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_is_int_index[8-u] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_deprecate_keyword[unchanged] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_is_float_index[4] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_dict_deprecate_kwarg[yes] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_is_int_index[1-u] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_deprecate_keyword[old] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_is_int_index[2-u] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_bad_deprecate_kwarg PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_missing_deprecate_kwarg[bogus] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_missing_deprecate_kwarg[-1.23] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_callable_deprecate_kwarg[-1.4] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_is_int_index[4-u] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_deprecate_kwarg[new-False] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_is_float_index[8] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_is_int_index[4-i] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_callable_deprecate_kwarg[1] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_dict_deprecate_kwarg[no] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_is_int_index[1-i] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_missing_deprecate_kwarg[12345] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_is_int_index[2-i] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_callable_deprecate_kwarg[0] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_is_int_index[8-i] PASSED [ 15%] statsmodels/compat/tests/test_pandas.py::test_deprecate_kwarg[old-True] PASSED [ 15%] statsmodels/tsa/statespace/tests/test_var.py::test_var_c PASSED [ 15%] statsmodels/tsa/statespace/tests/test_var.py::test_var_ct_as_exog1 PASSED [ 15%] statsmodels/tsa/statespace/tests/test_var.py::test_var_ct_as_exog0 PASSED [ 15%] statsmodels/tsa/statespace/tests/test_var.py::test_var_ctt PASSED [ 15%] statsmodels/tsa/statespace/tests/test_var.py::test_var_ct_exog PASSED [ 15%] statsmodels/tsa/statespace/tests/test_var.py::test_var_basic PASSED [ 15%] statsmodels/tsa/statespace/tests/test_var.py::test_var_c_2exog PASSED [ 15%] statsmodels/tsa/statespace/tests/test_var.py::test_var_ct PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movorder_string_order_max XFAILmary interface) is completely broken. `np.isfinite(order)` is called unconditionally before checking `order in ('med', 'min', 'max')`, and raises TypeError for any string order before the string branches are ever reached. Even the module's own check_movorder() self- test crashes on its first call for this reason. This test documents the *intended* behavior from the docstring/check_movorder(); it should start passing once the order dispatch is fixed to check string values before np.isfinite().) [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movvar_2d_is_columnwise[lagged-expected_slice2] PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movvar_2d_is_columnwise[centered-expected_slice1] PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movmean_leading_window_100_matches_regression_values PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movorder_invalid_lag_raises PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_expandarr_zero_padding_is_noop PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movmean_lagged_window_100_matches_regression_values PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movorder_string_order_min XFAIL.) [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movmoment_invalid_lag_raises PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movorder_string_order_med XFAIL.) [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movmean_equals_movmoment_order_1 PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movmean_1d_leading_matches_regression_values PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movorder_min_lagged_matches_decreasing_series PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movorder_min_centered PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_expandarr_1d PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movvar_1d[lagged-expected_slice2] PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movmoment_prints_debug_output PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_expandarr_2d PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movvar_equals_second_minus_first_squared_moment PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movmean_1d_lagged_matches_regression_values PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movmean_centered_window_101_matches_regression_values PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movvar_1d[leading-expected_slice0] PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movmean_1d_centered_matches_regression_values PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movvar_1d[centered-expected_slice1] PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movorder_invalid_order_raises_for_numeric_path PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movorder_max_lagged_matches_increasing_series PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movvar_2d_is_columnwise[leading-expected_slice0] PASSED [ 15%] statsmodels/sandbox/tsa/tests/test_movstat.py::test_movmean_2d_matches_1d_broadcast PASSED [ 15%] statsmodels/tsa/innovations/tests/test_arma_innovations.py::test_innovations_nonstationary[ar_params0] PASSED [ 15%] statsmodels/tsa/innovations/tests/test_arma_innovations.py::test_innovations_nonstationary[ar_params2] PASSED [ 15%] statsmodels/tsa/innovations/tests/test_arma_innovations.py::test_innovations_nonstationary[1.0] PASSED [ 15%] statsmodels/tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params4-ma_params4-1.123] PASSED [ 15%] statsmodels/tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params5-ma_params5-1.123] PASSED [ 15%] statsmodels/tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params0-ma_params0-1] PASSED [ 15%] statsmodels/tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params1-ma_params1-1] PASSED [ 15%] statsmodels/tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params2-ma_params2-1] PASSED [ 15%] statsmodels/tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params3-ma_params3-1] PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP_predict::test_predict_generic_zi PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP_predict::test_var PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP_predict::test_predict_prob PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP_predict::test_mean PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_llf PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_aic PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_params PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_bic PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_fit_regularized XFAIL [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_conf_int PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_null PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_bse PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_init_keys PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_t PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_summary PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_fit_regularized_invalid_method <- discrete/tests/test_discrete.py PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_minimize PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_bse PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_init_keys PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_t PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_aic PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_bic PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_llf PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_null PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_fit_regularized PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_summary PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_conf_int PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_fit_regularized_invalid_method <- discrete/tests/test_discrete.py PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_params PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_params PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_aic PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_bic PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_llf PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_bse PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_minimize PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_null PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_t PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_init_keys PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_conf_int PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_summary PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_fit_regularized_invalid_method <- discrete/tests/test_discrete.py PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_fit_regularized PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_init_keys PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_bse PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_fit_regularized_invalid_method <- discrete/tests/test_discrete.py PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_summary PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_conf_int PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_aic PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_bic PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_llf PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_null PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_fit_regularized PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_params PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_t PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedPoisson_predict::test_predict_options PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedPoisson_predict::test_var PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedPoisson_predict::test_predict_prob PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedPoisson_predict::test_mean PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson_predict::test_mean PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson_predict::test_predict_prob PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson_predict::test_var PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP_predict2::test_mean PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP_predict2::test_zero_nonzero_mean PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_llf PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_aic PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_bic PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_params PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_names PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_fit_regularized PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_bse PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_summary PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_init_keys PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_null PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_conf_int PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_t PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_fit_regularized_invalid_method <- discrete/tests/test_discrete.py PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::test_summary_after_remove_data[ZeroInflatedPoisson] PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::test_summary_after_remove_data[ZeroInflatedGeneralizedPoisson] PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::test_summary_after_remove_data[ZeroInflatedNegativeBinomialP] PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_conf_int PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_t PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_params PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_exposure PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_bse PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_aic PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_bic PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_llf PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_summary PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_init_keys PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_fit_regularized_invalid_method <- discrete/tests/test_discrete.py PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_null PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_fit_regularized PASSED [ 16%] statsmodels/discrete/tests/test_count_model.py::TestPandasOffset::test_pd_offset_exposure PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::TestProportion::test_default_values PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::TestProportion::test_scalar PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::TestProportion::test_pairwiseproptest PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::TestProportion::test_number_pairs_1493 PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::TestProportion::test_proptest PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_multinomial_proportions_sison_glaz_sparse[counts0] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[wilson-case7] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[wilson-case6] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_multinomial_proportions_sison_glaz_sparse[counts1] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion_ndim[wilson] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[wilson-case4] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_multinomial_proportions_zeros PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_samplesize_confidenceinterval_prop PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_multinomial_proportions_sison_glaz_sparse[counts3] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_multinomial_proportions_sison_glaz_sparse[counts2] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion_wilson_clip PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion_ndim[beta] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[wilson-case5] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[wilson-case0] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[wilson-case1] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion_ndim[jeffreys] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[wilson-case3] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion_ndim[normal] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[wilson-case2] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[beta-case6] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[agresti_coull-case7] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[normal-case6] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_multinomial_proportions PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[jeffreys-case1] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[jeffreys-case0] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_proportion_effect_size PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[beta-case7] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion_ndim[agresti_coull] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[agresti_coull-case6] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[normal-case7] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[jeffreys-case2] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[beta-case5] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[normal-case5] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[agresti_coull-case4] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[beta-case4] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[normal-case4] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[agresti_coull-case5] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_multinomial_proportions_sison_glaz_sparse_r_reference PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[jeffreys-case3] SKIPPED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[jeffreys-case6] SKIPPED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[normal-case1] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[agresti_coull-case0] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[beta-case1] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[normal-case0] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[agresti_coull-case1] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[beta-case0] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[jeffreys-case7] SKIPPED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[agresti_coull-case3] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[normal-case2] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[beta-case2] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[jeffreys-case5] SKIPPED [ 16%] statsmodels/stats/tests/test_proportion.py::test_multinomial_proportions_errors PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[jeffreys-case4] SKIPPED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[agresti_coull-case2] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[normal-case3] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_confint_proportion[beta-case3] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count23-47] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count16-50] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count33-50] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count13-47] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count26-50] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count9-47] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count11] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count36-47] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count9] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count29-50] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count7] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count39-47] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count0-47] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count19-50] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count9] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count3-50] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count1] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count11] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count30-47] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count3] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_int_check PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count9-47] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count6] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count20-50] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count15-47] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count35-50] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_binom_test[0.01-smaller-expected6-1e-07-200-100] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count10-50] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count5] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count25-47] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count8] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count3-50] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count6] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count0-47] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[jeffreys-0.05-larger-expected11-200-100] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count7] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count2] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count4] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_edge[0-1-smaller-expected5] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count40-47] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count9] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count7] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count45-50] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[beta-0.05-smaller-expected14-200-100] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count10] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_edge[1-1-smaller-expected4] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count43-50] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count8] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count6] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count8] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count10] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count0] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count46-47] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count6] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[normal-0.05-smaller-expected12-200-100] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[wilson-0.05-smaller-expected15-200-100] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count42-50] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_edge[1-1-two-sided-expected0] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count5] PASSED [ 16%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count0] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count47-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_binom_test[0.01-two-sided-expected0-0.0001-200-100] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count5] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_score_confint_koopman_nam PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count41-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count12] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count14] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count44-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count15] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count12] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count2] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_test_2indep PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count4] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count13] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count15] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count2-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count1-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count21-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count14-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count14] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count31-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_equivalence_2indep PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count3] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count13] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count8-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count11-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_binom_test[0.05-smaller-expected7-1e-07-200-100] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count5] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count24-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count34-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count38-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count1-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count28-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count7] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count1] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count2-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count18-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count4] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count4] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count32-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count22-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count17-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count37-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_samplesize_proportions_2indep_onetail_alternative PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count8-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_power_ztost_prop PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count12-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count27-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count0-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count1] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count3-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[beta-0.05-two-sided-expected4-200-100] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_proportion_ztests PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count35-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count2] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_confint_2indep_propcis PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count25-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ztost PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count10-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count9-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count1] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count30-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count15-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count4] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count20-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count11] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count19-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count6] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count3-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count29-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count0-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count8] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count39-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count0] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count26-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count10] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count13-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count8] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count9-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count36-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count16-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count23-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count33-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count46-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count10] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count7] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count9] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count1] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count43-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count9] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_binom_test_alternative_deprecated_alias PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count11] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count0] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[wilson-0.05-two-sided-expected5-200-100] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count45-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_binom_test_reject_interval_alternative PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[agresti_coull-0.05-two-sided-expected3-200-100] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count40-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count3] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count5] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count0] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count3] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count12] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count15] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count5] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count44-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count9] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_power_binom_tost PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count41-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count15] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count13] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[wilson-0.05-larger-expected10-200-100] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[agresti_coull-0.05-smaller-expected13-200-100] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count2] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count7] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count47-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count2] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count1] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count42-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count37-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count8-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count27-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count12-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count32-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count3] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[agresti_coull-0.05-larger-expected8-200-100] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count17-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count22-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count3] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count2-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count6] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count18-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count1-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count0] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count38-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count28-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count24-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count11-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count34-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count2] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count13] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count14-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count21-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count4] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count14] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count8-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count31-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count1-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count8] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count14] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count12] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count2-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_edge[1-1-larger-expected2] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count6] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count29-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count39-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count6-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count12] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count13] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count19-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count8] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count6] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count0] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count5-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count16-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[jeffreys-0.05-two-sided-expected6-200-100] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_power_2indep PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count23-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count33-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count0] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count26-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count13-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count10] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count36-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count10] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count2] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count10] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count12] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count5-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count9] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count6-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count7] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count30-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count15-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[normal-0.05-two-sided-expected0-200-100] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_binom_rejection_interval PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count20-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count35-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count9] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count25-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count15] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count10-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[normal-0.1-two-sided-expected2-200-100] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[jeffreys-count8] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count40-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count13] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count6] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[normal-0.01-two-sided-expected1-200-100] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count45-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count14] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count8] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count43-50] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count7] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count46-47] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count9] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count7] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count1] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count13] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count12] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count1] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count11] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count3] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count11] PASSED [ 17%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count11] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[normal-0.05-larger-expected7-200-100] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_confint_2indep PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count4] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_binom_test[0.1-larger-expected5-1e-07-200-100] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count14] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count11] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count42-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count9] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count47-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count3] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count5] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count10] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count11] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count5] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count13] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count13] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count1] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count13] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count41-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count44-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count3] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count11] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count14-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count10] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count21-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[beta-0.05-larger-expected9-200-100] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count2] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count4] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count31-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count24-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count11-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count4] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count34-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count12] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count0] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count12] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count4-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count12] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_binom_test[0.1-smaller-expected8-1e-07-200-100] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count7-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count2] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count32-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count15] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count5] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count17-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count22-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_edge[0-1-two-sided-expected1] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count37-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count10] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count27-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count12-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_binom_test[0.1-two-sided-expected2-0.0001-200-100] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count7-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count38-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count28-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count8] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count4-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count18-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count12] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count35-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count10-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count25-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count30-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count20-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count15-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count0] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count6-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint[jeffreys-0.05-smaller-expected16-200-100] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count10] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count5-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_invalid_alternative_raises PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_score_test_2indep PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count15] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count5] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count13-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count26-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count36-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_binom_test[0.05-two-sided-expected1-0.0001-200-100] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count23-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count7] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count16-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count33-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count19-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count1] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count7] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count15] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count14] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count5-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count29-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count39-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count6-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count9] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_power_ztost_prop_norm PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count1] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count4] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count6] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count14] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count15] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count46-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count0] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count6] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count43-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count8] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count0] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_binom_tost PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_proportions_chisquare_pairscontrol_alternative PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count13] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_binom_test PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count11] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count1] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_binom_test[0.01-larger-expected3-1e-07-200-100] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count45-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[jeffreys-count14] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count40-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count44-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count4] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count41-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count14] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count6] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count14] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count14] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count2] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count4] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count2] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count47-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count11] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count42-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count8] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count13] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count3] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count4-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count18-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count7-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[wilson-count10] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count38-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count9] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count28-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count37-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count12-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count27-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count32-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count2] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count22-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[normal-count12] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count17-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[wilson-count5] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_edge[0-1-larger-expected3] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count7-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[binom_test-count7] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[agresti_coull-count15] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[beta-count15] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[normal-count15] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count4-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_proportion_confint_binom_test[0.05-larger-expected4-1e-07-200-100] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count11-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count24-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count34-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[binom_test-count3] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count21-47] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[False-count14-50] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_array[beta-count5] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry[agresti_coull-count3] PASSED [ 18%] statsmodels/stats/tests/test_proportion.py::test_ci_symmetry_binom_test[True-count31-50] PASSED [ 18%] statsmodels/tsa/interp/tests/test_denton.py::test_denton_quarterly2 PASSED [ 18%] statsmodels/tsa/interp/tests/test_denton.py::test_denton_freq_qm_matches_benchmark_sums PASSED [ 18%] statsmodels/tsa/interp/tests/test_denton.py::test_denton_freq_other_requires_k PASSED [ 18%] statsmodels/tsa/interp/tests/test_denton.py::test_denton_invalid_freq_raises PASSED [ 18%] statsmodels/tsa/interp/tests/test_denton.py::test_denton_freq_other_matches_benchmark_sums PASSED [ 18%] statsmodels/tsa/interp/tests/test_denton.py::test_denton_quarterly PASSED [ 18%] statsmodels/imputation/tests/test_bayes_mi.py::test_2x2 PASSED [ 18%] statsmodels/imputation/tests/test_bayes_mi.py::test_MI_stat PASSED [ 18%] statsmodels/imputation/tests/test_bayes_mi.py::test_pat PASSED [ 18%] statsmodels/imputation/tests/test_bayes_mi.py::test_MI PASSED [ 18%] statsmodels/imputation/tests/test_bayes_mi.py::test_mi_formula PASSED [ 18%] statsmodels/emplike/tests/test_aft.py::Test_AFTModel::test_betaci PASSED [ 18%] statsmodels/emplike/tests/test_aft.py::Test_AFTModel::test_predict PASSED [ 18%] statsmodels/emplike/tests/test_aft.py::Test_AFTModel::test_beta1 PASSED [ 18%] statsmodels/emplike/tests/test_aft.py::Test_AFTModel::test_beta0 PASSED [ 18%] statsmodels/emplike/tests/test_aft.py::Test_AFTModel::test_beta_vect PASSED [ 18%] statsmodels/emplike/tests/test_aft.py::Test_AFTModel::test_params PASSED [ 18%] statsmodels/tools/tests/test_web.py::TestWeb::test_string PASSED [ 18%] statsmodels/tools/tests/test_web.py::TestWeb::test_nothing PASSED [ 18%] statsmodels/tools/tests/test_web.py::TestWeb::test_function PASSED [ 18%] statsmodels/tools/tests/test_web.py::TestWeb::test_errors PASSED [ 18%] 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statsmodels/stats/tests/test_qsturng.py::test_qstrung[k4-0.01] PASSED [ 20%] statsmodels/tools/tests/test_tools.py::TestEnsure2d::test_numpy PASSED [ 20%] statsmodels/tools/tests/test_tools.py::TestEnsure2d::test_enfore_numpy PASSED [ 20%] statsmodels/tools/tests/test_tools.py::TestEnsure2d::test_pandas PASSED [ 20%] statsmodels/tools/tests/test_tools.py::TestTools::test_add_constant_1d PASSED [ 20%] statsmodels/tools/tests/test_tools.py::TestTools::test_add_constant_list PASSED [ 20%] statsmodels/tools/tests/test_tools.py::TestTools::test_recipr0 PASSED [ 20%] statsmodels/tools/tests/test_tools.py::TestTools::test_fullrank PASSED [ 20%] statsmodels/tools/tests/test_tools.py::TestTools::test_recipr PASSED [ 20%] statsmodels/tools/tests/test_tools.py::TestTools::test_extendedpinv_singular PASSED [ 20%] statsmodels/tools/tests/test_tools.py::TestTools::test_add_constant_series PASSED [ 20%] statsmodels/tools/tests/test_tools.py::TestTools::test_drop_missing PASSED [ 20%] 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statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_mfx_nonlinear_ll_cvls XFAIL [ 20%] statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_censored_user_specified_kernel PASSED [ 20%] statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_censored_ll_cvls PASSED [ 20%] statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_significance_seed_legacy PASSED [ 20%] statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_continuousdata_lc_cvls PASSED [ 20%] statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_user_specified_kernel PASSED [ 20%] statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_significance_seed_thread_safe PASSED [ 20%] statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_significance_seed PASSED [ 20%] 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statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_ppplot PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_probplot_custom_labels PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_qqplot PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_exceptions PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_ppplot_other_array PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_fit_params PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_ppplot_custom_labels PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_probplot PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_qqplot_other_prbplt 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statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_qqplot_custom_labels PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot_other_array PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_qqplot_pltkwargs PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_ppplot_pltkwargs PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot_other_prbplt PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot_exceed PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_qqplot PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_ppplot_other_array PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_qqplot_other_array PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_qqplot_other_prbplt PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot_pltkwargs PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_ppplot_custom_labels PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_ppplot_other_prbplt PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot_custom_labels PASSED [ 21%] statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_loc_set PASSED [ 21%] 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statsmodels/robust/tests/test_rlm.py::TestHampel::test_degrees PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampel::test_summary PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampel::test_scale PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampel::test_bcov_scaled PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampel::test_params PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampel::test_chisq PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampel::test_predict PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampel::test_tpvalues PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampel::test_residuals PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampel::test_summary2 PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampel::test_confidenceintervals SKIPPED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampel::test_bcov_unscaled PASSED [ 22%] 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statsmodels/robust/tests/test_rlm.py::TestRlm::test_bcov_scaled PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlm::test_residuals PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlm::test_tpvalues PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlm::test_predict PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmBisquare::test_confidenceintervals SKIPPED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmBisquare::test_scale PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmBisquare::test_weights PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmBisquare::test_tvalues PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmBisquare::test_summary2 PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmBisquare::test_params PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmBisquare::test_chisq PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmBisquare::test_residuals PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmBisquare::test_standarderrors PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmBisquare::test_tpvalues PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmBisquare::test_bcov_unscaled PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmBisquare::test_predict PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmBisquare::test_bcov_scaled PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmBisquare::test_summary PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmBisquare::test_degrees PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_perfect_fit[HuberT] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_perfect_const[HuberT] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_rlm_start_values_errors PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_rlm_scale_est_one_and_two_inputs PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_perfect_fit[TrimmedMean] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_perfect_const[TrimmedMean] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_perfect_fit[TukeyBiweight] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_perfect_const[TukeyBiweight] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_rlm_results_direct_construction_validates_cov PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_rlm_scale_est_callback_receives_model PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_fit_invalid_options_raise PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_rlm_scale_est_resid_callable_df_correction PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_fit_history_scale PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_perfect_fit[LeastSquares] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_perfect_const[LeastSquares] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_perfect_fit[AndrewWave] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_perfect_const[AndrewWave] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_perfect_fit[Hampel] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_perfect_const[Hampel] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_perfect_fit[RamsayE] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_perfect_const[RamsayE] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_summary_after_remove_data PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_alt_criterion[coefs] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_alt_criterion[weights] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_bad_criterion PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_rlm_start_values PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_missing PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_summary_title PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::test_alt_criterion[sresid] PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmHuber::test_confidenceintervals PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmHuber::test_residuals PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmHuber::test_standarderrors PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmHuber::test_tpvalues PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmHuber::test_bcov_unscaled SKIPPED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmHuber::test_tvalues SKIPPED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmHuber::test_weights PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmHuber::test_degrees PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmHuber::test_params PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmHuber::test_scale PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmHuber::test_bcov_scaled PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_standarderrors PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_residuals PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_tpvalues PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_weights PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_tvalues PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_scale PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_degrees PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_bcov_scaled PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_confidenceintervals SKIPPED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_bcov_unscaled PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_params PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampelHuber::test_summary2 PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampelHuber::test_weights PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampelHuber::test_tvalues SKIPPED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampelHuber::test_residuals PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampelHuber::test_params PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampelHuber::test_bcov_unscaled SKIPPED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampelHuber::test_scale PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampelHuber::test_standarderrors PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampelHuber::test_predict PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampelHuber::test_confidenceintervals PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampelHuber::test_summary PASSED [ 22%] statsmodels/robust/tests/test_rlm.py::TestHampelHuber::test_degrees PASSED [ 23%] statsmodels/robust/tests/test_rlm.py::TestHampelHuber::test_tpvalues PASSED [ 23%] statsmodels/robust/tests/test_rlm.py::TestHampelHuber::test_chisq PASSED [ 23%] statsmodels/robust/tests/test_rlm.py::TestHampelHuber::test_bcov_scaled PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test_vectorized[ratio-cond-midp] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test[diff-etest-wald] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test[ratio-exact-cond] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_confint[diff-score] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test_vectorized[diff-score] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test_vectorized[ratio-exact-cond] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test[diff-score] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test_vectorized[diff-wald] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test[ratio-wald-log] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test[diff-wald] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_confint[ratio-wald-log] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test_vectorized[ratio-etest-score] SKIPPED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_confint[diff-wald] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test_vectorized[ratio-wald-log] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test[diff-etest-score] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test_vectorized[diff-waldccv] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test_vectorized[diff-etest-score] SKIPPED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test_vectorized[ratio-etest-wald] SKIPPED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test[ratio-etest-wald] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_confint[ratio-score] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test_vectorized[ratio-sqrt] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test[ratio-cond-midp] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test[ratio-sqrt] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test_vectorized[diff-etest-wald] SKIPPED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test[diff-waldccv] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test[ratio-etest-score] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test_vectorized[ratio-wald] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test_vectorized[ratio-score-log] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test[ratio-wald] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_confint[ratio-mover] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test[ratio-score] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_confint[ratio-sqrtcc] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_confint[diff-waldccv] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_confint[ratio-waldcc] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_confint[diff-mover] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_confint[ratio-score-log] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test_vectorized[ratio-score] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompare2indep::test_test[ratio-score-log] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_test[score] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_test[wald] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_confint[sqrt-centcc] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_confint[exact-c] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_confint[sqrt-cent] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_confint[jeff] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_confint[midp-c] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_test[midp-c] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_confint[waldccv] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_confint[wald] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_confint[sqrt] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_confint[score] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_test[waldccv] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_test[sqrt] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_confint[sqrt-a] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_test[sqrt-v] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_test[exact-c] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_confint[sqrt-v] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::TestMethodsCompar1samp::test_test[sqrt-a] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_tol_int[case4] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_consistency[wald] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_consistency[exact-c] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_consistency[sqrt-a] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_consistency[sqrt-v] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_tol_int[case3] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_tol_int[case2] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_tol_int[case0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_consistency[waldccv] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_consistency[score] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_tol_int[case1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_consistency[midp-c] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_consistency[sqrt] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_r PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case12] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case5] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_diff_consistency[wald] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case4] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case13] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_diff_ratio_consistency[etest] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case6] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_diff_ratio_consistency[score] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case11] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case20] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case7] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_diff_consistency[score] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case2] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case15] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case14] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_ratio_consistency[score-log] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case3] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_twosample_poisson_r PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case16] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_diff_ratio_consistency[etest-wald] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case17] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_twosample_poisson_diff[case0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_diff_consistency[waldccv] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_twosample_poisson_diff[case1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_twosample_poisson PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case9] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_twosample_poisson_diff[case3] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case8] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_twosample_poisson_diff[case2] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_ratio_consistency[wald-log] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_tost_poisson PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_2indep PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case19] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_rate_poisson_diff_ratio_consistency[wald] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_alternative[case18] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.1-100-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.05-100-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.05-1-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.05-100-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.01-1-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.1-1-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.05-1-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-100-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.1-100-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.05-100-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.1-10-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.1-1-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.1-10-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.1-100-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.01-100-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.01-1-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.1-10-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.01-1-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.01-1000-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.1-1-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.05-10-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.1-1-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.01-100-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.05-1-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.05-1000-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.05-1000-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-10-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.01-1000-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.05-1000-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.01-1000-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.1-10-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.01-1000-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.1-1-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.05-1-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.01-1-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.05-10-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.05-10-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.01-100-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.1-10-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.1-1-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.05-100-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.05-1000-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.01-100-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.1-1000-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.1-100-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.05-100-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.01-1000-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.01-100-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.05-100-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.1-10-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_y_grid_regression PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.05-100-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.01-10-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.1-10-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.05-1000-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.05-100-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.05-1-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.01-100-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.05-100-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.1-1-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.01-1-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.01-1000-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.01-1-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.1-1000-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.1-10-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.05-100-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.05-100-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.1-1-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.05-1000-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.01-1-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.05-10-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.01-1-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.05-100-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.01-100-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.1-10-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.1-10-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.1-100-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.1-1000-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.1-1-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.05-100-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.01-10-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.05-10-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.05-100-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.05-1-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.1-1000-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-1-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.1-1-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.05-100-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.01-100-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.1-1000-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.01-10-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.1-10-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.1-1000-100] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.1-1000-10] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.1-100-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.1-100-0] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.05-100-1] PASSED [ 23%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.01-1-0] PASSED [ 23%] 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statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.1-1-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.05-100-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.01-100-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.01-1000-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.05-100-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.05-1000-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.1-10-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.01-100-0] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.01-1-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-10-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.1-1000-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.01-100-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.05-1000-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.05-1-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.05-10-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.05-1000-100] PASSED [ 24%] 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statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.05-10-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.01-1-0] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.1-1000-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.01-10-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.1-1000-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.01-1-0] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.01-1000-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.05-1-100] PASSED [ 24%] 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statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.01-10-0] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.05-1-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-100-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.05-1-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.01-10-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.01-10-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.05-10-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.01-100-100] PASSED [ 24%] 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statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.1-1000-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.01-10-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.01-100-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.01-100-0] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.05-100-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.01-100-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.05-1000-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.1-100-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.01-1-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.1-1000-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.05-1-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.05-10-0] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.01-1-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.1-1000-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.01-1000-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.05-1-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.05-1-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.1-1-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.01-1-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.01-100-0] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.05-10-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.01-10-0] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.05-1-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.01-10-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.05-10-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.05-100-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.1-10-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.1-1-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.05-100-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.01-1-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.01-10-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.01-1000-100] PASSED [ 24%] 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statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.01-100-0] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.05-100-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.1-1000-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.1-10-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.05-10-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.05-1000-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.1-100-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.01-100-10] PASSED [ 24%] 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statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.01-10-0] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.01-1-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.1-1-1] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.1-10-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.01-100-10] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.05-1000-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.01-1-100] PASSED [ 24%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.05-100-0] PASSED [ 24%] 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statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.01-10-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.1-1000-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.1-1000-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.01-10-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.01-1000-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.01-10-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.1-100-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.01-100-1] PASSED [ 25%] 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statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.05-1000-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.1-1000-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.1-1-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.01-100-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.1-1000-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.05-1-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.1-1-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.1-1-100] PASSED [ 25%] 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statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.05-100-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.01-1000-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.01-1-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.05-100-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.05-10-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.1-1000-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.1-100-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.05-1000-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.05-100-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-100-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.05-10-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.1-1-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.01-10-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-1-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.1-1000-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.05-1000-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.1-1-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.01-100-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.01-10-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.1-1-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.1-1-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.01-1-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.05-10-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.1-100-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.01-10-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.1-1000-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.1-100-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.05-1-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.01-1-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.1-1000-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.1-100-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.01-1-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.1-1-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.1-100-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.1-1000-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.1-10-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.05-10-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.01-100-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.05-1-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.1-10-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.01-1000-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.1-1000-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.01-10-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.01-10-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.1-1000-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.1-100-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.01-10-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.1-1-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.01-1-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.1-1000-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.01-1-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.01-1-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.1-1-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.01-100-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.01-1-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.01-10-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.05-100-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.01-1-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.01-1-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.1-1-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.05-1-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.05-10-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.05-10-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.1-1-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.01-10-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.05-1000-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.01-10-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.01-10-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.05-1000-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.05-1-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.1-100-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.1-1-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-1000-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.05-1-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.01-10-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.1-1000-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.05-1000-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.05-10-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.1-1-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.1-1000-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.05-1-0] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-10-100] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.05-10-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.1-1000-1] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.05-1000-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.05-1-10] PASSED [ 25%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.01-100-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.05-1000-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.1-100-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.1-100-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-1-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.1-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.01-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.01-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-1-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.05-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.05-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.01-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.01-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.1-1-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.1-10-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.05-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.1-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.05-100-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.05-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.01-1-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.05-1-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.01-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.01-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.05-1-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.01-10-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.01-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.01-100-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.05-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.05-10-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.01-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.1-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.01-1000-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.05-1-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.05-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.05-1-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.05-100-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.01-100-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.01-1-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.05-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.1-10-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.01-10-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.01-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.01-100-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.05-10-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.05-10-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.05-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_poisson_invalid_alternative_raises PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.01-1-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.05-1-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.05-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.05-1000-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_poisson_power_2ratio PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.01-100-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.1-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.01-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.01-100-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.01-10-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.01-10-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.1-100-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.01-1000-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.05-10-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.01-100-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.05-100-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.05-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.01-1-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.05-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.1-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.05-1-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.01-100-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.05-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.05-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.01-100-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.01-1000-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.01-1-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.1-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.05-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.1-1000-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.05-1-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.01-1000-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.01-100-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.1-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.05-10-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.1-100-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.05-1000-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.01-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.05-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.1-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-1-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.01-1-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-1000-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.01-10-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.1-1000-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.05-1-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.01-1000-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.1-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.05-1-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.1-100-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.1-1000-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.05-1-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.1-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.1-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.05-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.01-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.01-100-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.1-100-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.1-100-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.05-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.1-10-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-1-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.01-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.01-1-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.05-1-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.01-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.01-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.1-1-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.05-10-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.1-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.05-100-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.05-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.1-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.05-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.01-1-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.1-1-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.01-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.05-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.05-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.1-100-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-10-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.05-10-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.01-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.05-100-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.05-1-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.1-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.01-1-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.05-1-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_etest_poisson_2indep_alternative_deprecated_alias[s-smaller] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.01-1-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.05-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.1-10-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.01-1000-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.05-1-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.01-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.05-10-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.05-1-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.05-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_power_negbin PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.05-100-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.01-1-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.05-10-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.05-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.01-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.1-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-1000-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.05-10-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.05-1-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-100-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.05-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.01-100-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.1-1-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.05-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.01-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.05-1000-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.05-100-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.05-100-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.1-10-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.01-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.01-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.05-1000-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.01-1000-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.1-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.05-1-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.01-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.1-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.05-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.1-10-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.1-1-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.05-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.1-100-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-100-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.1-1-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.01-10-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.05-1000-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.01-1000-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.1-1-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.1-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.05-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.1-1-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.1-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.1-10-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.05-1000-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.1-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.01-1-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.1-1-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.1-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.05-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.01-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.1-1-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.01-100-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.05-1-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.05-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-100-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.01-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_invalid_y_grid PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.05-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.01-1000-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.01-1000-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.05-100-10] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.01-100-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.05-10-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.05-100-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.05-100-0] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.05-1000-100] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.1-10-1] PASSED [ 26%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.01-10-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.05-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.1-1-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.01-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.1-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.01-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.05-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.1-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.1-1-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.05-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.1-10-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.1-100-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.1-1-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-100-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.01-1000-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.1-10-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.1-1-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.05-10-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.05-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.01-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.1-100-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.05-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.05-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-10-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.01-10-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.01-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.05-1000-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.05-10-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.05-1-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.05-1-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.05-100-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.05-100-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.1-10-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.05-1-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.1-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.01-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.1-1-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.05-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.01-1-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.1-10-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.05-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.1-10-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.1-100-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.01-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.05-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.01-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.1-1-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.05-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.05-100-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_power_poisson_equal PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.05-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.1-1000-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.05-100-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.05-1-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.05-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.01-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.05-100-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.01-10-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.01-10-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.01-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.1-100-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.01-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.05-1-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.05-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.1-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.01-100-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.01-1-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.05-1-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.01-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.05-10-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.05-10-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_etest_poisson_2indep_alternative_deprecated_alias[l-larger] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.1-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.05-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.1-100-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.01-100-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-1-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.01-10-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.1-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.05-10-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.01-100-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.1-1-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.05-100-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.1-100-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.01-10-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.01-1-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.1-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.1-100-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.1-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.05-1-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.01-1-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.01-10-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.01-100-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.1-1-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.1-1000-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.05-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.01-1-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.05-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.05-10-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.05-100-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.05-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.05-1-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.05-1-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.1-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.05-1-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.1-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.01-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.05-100-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.01-100-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.1-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.01-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.01-10-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.01-1-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.01-1-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.1-100-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.01-1-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.01-1-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.01-10-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.1-10-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.1-10-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.01-10-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.01-1000-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.05-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.05-1-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.05-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.01-1-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.01-1-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.1-10-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.01-10-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.01-100-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.05-10-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.1-1-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.1-10-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.05-10-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.01-10-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.05-1-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.1-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.1-1000-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.1-10-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.01-10-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.01-1-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.01-1-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.01-10-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.01-1-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.01-1-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.05-10-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.01-100-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.1-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-score-0.1-100-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.05-10-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.05-1-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.05-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.1-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.01-100-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.01-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.01-1-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.05-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.05-100-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.01-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.01-10-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.1-100-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.1-10-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.1-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.05-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.1-1-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.01-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.1-1000-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.1-100-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.05-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.05-10-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.01-1-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.01-10-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.1-1-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.1-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.1-1-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.05-100-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.01-100-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-1-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.05-1000-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.01-1000-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.1-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-10-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.01-1-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_power_2indep_invalid_method_var_raises PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.01-100-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.1-100-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.05-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.01-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.05-1-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.05-1-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.05-1-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.01-1000-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.01-100-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.05-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.05-1000-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.05-1-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.01-100-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.01-100-10] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.05-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.01-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.1-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.01-10-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.05-100-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.01-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.01-1000-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.1-100-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.1-100-1] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.05-100-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.1-1000-0] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.1-100-100] PASSED [ 27%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.05-1000-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.1-1-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-1000-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.1-10-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.05-100-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.05-1-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.1-100-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.1-10-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.01-1000-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.1-100-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.01-1000-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.05-1000-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.05-1000-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.05-1-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.05-100-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.01-10-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.1-10-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.05-100-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.01-1-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.1-10-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.1-10-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.05-10-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.01-10-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.05-10-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.1-1-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.01-1-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.1-10-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.05-1000-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.05-100-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.05-100-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.05-1-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.05-10-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.01-1000-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_etest_poisson_2indep_alternative_deprecated_alias[2s-two-sided] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.1-100-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.1-10-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.1-1-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.05-10-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.1-100-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.01-10-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.01-1000-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.1-10-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.01-100-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.1-100-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.05-1000-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.01-100-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.05-1000-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.01-1-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-centcc-0.05-1-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.1-10-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.1-100-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.01-1000-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.1-10-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.01-1000-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.05-1-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.1-10-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.05-1000-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.05-100-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-exact-c-0.01-1-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.01-1000-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.05-100-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.1-1-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.1-100-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.1-10-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.1-10-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.05-100-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.1-10-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.05-1000-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.05-1000-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.05-1000-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.1-1000-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-wald-0.01-10-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-centcc-0.1-10-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.05-10-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.01-1000-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.1-1-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.1-10-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-cent-0.1-100-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-waldccv-0.05-1-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.05-1-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.01-100-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-midp-c-0.05-1000-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.01-1-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.1-10-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.1-100-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.01-1000-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.05-10-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.05-1-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-waldccv-0.05-1000-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_poisson_2indep_invalid_compare_raises PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-cent-0.01-1000-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.01-100-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.1-100-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.05-10-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.05-1-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-score-0.1-10-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-0.01-10-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.05-100-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-wald-0.01-1-10] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-midp-c-0.1-100-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-jeff-0.01-1000-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.01-1000-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-a-0.1-100-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.1-100-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-a-0.01-1000-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-0.01-1-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-exact-c-0.05-100-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.05-1-0] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[larger-sqrt-v-0.1-1000-100] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-sqrt-v-0.1-1000-1] PASSED [ 28%] statsmodels/stats/tests/test_rates_poisson.py::test_confint_poisson_alternative[smaller-jeff-0.05-10-10] PASSED [ 28%] statsmodels/stats/tests/test_base.py::test_holdertuple PASSED [ 28%] statsmodels/stats/tests/test_base.py::test_holdertuple2 PASSED [ 28%] statsmodels/stats/tests/test_base.py::test_allpairsresults_summary_pval_table PASSED [ 28%] statsmodels/tools/tests/test_transform_model.py::test_standardize_ols[5] PASSED [ 28%] statsmodels/tools/tests/test_transform_model.py::test_standardize_ols[1] PASSED [ 28%] statsmodels/tools/tests/test_transform_model.py::test_standardize1 PASSED [ 28%] statsmodels/nonparametric/tests/test_kernels.py::TestEpan::test_smoothconf PASSED [ 28%] statsmodels/nonparametric/tests/test_kernels.py::TestEpan::test_smoothconf_data PASSED [ 28%] statsmodels/nonparametric/tests/test_kernels.py::TestTriangular::test_smoothconf_data PASSED [ 28%] statsmodels/nonparametric/tests/test_kernels.py::TestTriangular::test_smoothconf PASSED [ 28%] statsmodels/nonparametric/tests/test_kernels.py::TestCosine::test_smoothconf XFAIL [ 28%] statsmodels/nonparametric/tests/test_kernels.py::TestCosine::test_smoothconf_data PASSED [ 28%] statsmodels/nonparametric/tests/test_kernels.py::TestGau::test_smoothconf_data PASSED [ 28%] statsmodels/nonparametric/tests/test_kernels.py::TestGau::test_smoothconf PASSED [ 28%] statsmodels/nonparametric/tests/test_kernels.py::TestUniform::test_smoothconf PASSED [ 28%] statsmodels/nonparametric/tests/test_kernels.py::TestUniform::test_smoothconf_data PASSED [ 28%] statsmodels/nonparametric/tests/test_kernels.py::test_tricube PASSED [ 28%] statsmodels/nonparametric/tests/test_kernels.py::TestBiweight::test_smoothconf_data PASSED [ 28%] statsmodels/nonparametric/tests/test_kernels.py::TestBiweight::test_smoothconf PASSED [ 28%] statsmodels/distributions/tests/test_bernstein.py::TestBernsteinBeta2dd::test_rvs PASSED [ 28%] statsmodels/distributions/tests/test_bernstein.py::TestBernsteinBeta2dd::test_basic PASSED [ 28%] statsmodels/distributions/tests/test_bernstein.py::test_bernstein_distribution_1d PASSED [ 28%] statsmodels/distributions/tests/test_bernstein.py::test_bernstein_distribution_2d PASSED [ 28%] statsmodels/distributions/tests/test_bernstein.py::TestBernsteinBeta2d::test_basic PASSED [ 28%] statsmodels/distributions/tests/test_bernstein.py::TestBernsteinBeta2d::test_rvs PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[bias] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input[bias] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_stde_axis PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_ic_equivalence[aic-aic_sigma] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input[maxabs] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[iqr] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_eval_measures PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[vare] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input[meanabs] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input[vare] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input[iqr] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input[medianbias] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[maxabs] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_iqr_axis PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_ic PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_ic_equivalence[bic-bic_sigma] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_ic_equivalence[aicc-aicc_sigma] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input[rmspe] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[rmspe] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[medianabs] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[mse] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_stde PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input[rmse] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[rmse] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input[medianabs] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_ic_equivalence[hqic-hqic_sigma] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[medianbias] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[meanabs] PASSED [ 28%] statsmodels/tools/tests/test_eval_measures.py::test_measures_empty_input[mse] PASSED [ 28%] statsmodels/tsa/vector_ar/tests/test_var_jmulti.py::test_fc PASSED [ 28%] statsmodels/tsa/vector_ar/tests/test_var_jmulti.py::test_normality PASSED [ 28%] statsmodels/tsa/vector_ar/tests/test_var_jmulti.py::test_causality PASSED [ 28%] statsmodels/tsa/vector_ar/tests/test_var_jmulti.py::test_impulse_response PASSED [ 28%] statsmodels/tsa/vector_ar/tests/test_var_jmulti.py::test_log_like PASSED [ 28%] statsmodels/tsa/vector_ar/tests/test_var_jmulti.py::test_whiteness PASSED [ 28%] statsmodels/tsa/vector_ar/tests/test_var_jmulti.py::test_ols_coefs PASSED [ 28%] statsmodels/tsa/vector_ar/tests/test_var_jmulti.py::test_lag_order_selection PASSED [ 28%] statsmodels/tsa/vector_ar/tests/test_var_jmulti.py::test_ols_det_terms PASSED [ 28%] statsmodels/tsa/vector_ar/tests/test_var_jmulti.py::test_exceptions PASSED [ 28%] statsmodels/tsa/vector_ar/tests/test_var_jmulti.py::test_ols_sigma PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::TestDecompose::test_2d PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::TestDecompose::test_interpolate_trend PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::TestDecompose::test_extrapolate_trend_invalid_string_raises PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::TestDecompose::test_raises PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::TestDecompose::test_pandas_nofreq PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::TestDecompose::test_pandas PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::TestDecompose::test_one_sided_moving_average_in_stl_decompose PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::TestDecompose::test_filt PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::TestDecompose::test_ndarray PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::TestDecompose::test_extrapolate_trend_freq_deprecated PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_smoke PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[True-False-12-multiplicative] PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[False-True-4-additive] PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[True-True-12-additive] PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[True-True-4-multiplicative] PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[True-True-12-multiplicative] PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[False-False-4-additive] PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[False-False-12-multiplicative] PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[False-True-4-multiplicative] PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_too_short PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_multiple PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[True-False-4-multiplicative] PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[True-False-12-additive] PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[True-False-4-additive] PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[False-False-12-additive] PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[False-False-4-multiplicative] PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[True-True-4-additive] PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[False-True-12-additive] PASSED [ 28%] statsmodels/tsa/tests/test_seasonal.py::test_seasonal_decompose_plot[False-True-12-multiplicative] PASSED [ 28%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::TestSmoothPlainFloatVsNumpyScalar::test_smooth_with_numpy_scalar_query_point_works PASSED [ 28%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::TestSmoothPlainFloatVsNumpyScalar::test_smooth_with_plain_float_query_point_raises XFAIL scalar) triggers `TypeError: unsupported operand type(s) for -: 'tuple' and 'float'` inside smooth(), for any kernel with a bounded domain (Epanechnikov, Uniform, Triangular, Cosine, Cosine2, Tricube, Triweight -- everything except Gaussian, whose domain is None, and Biweight, which overrides smooth() with its own implementation that doesn't call in_domain's buggy path the same way).) [ 28%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::TestInDomain::test_empty_result_when_nothing_in_domain PASSED [ 28%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::TestInDomain::test_filters_points_outside_domain PASSED [ 28%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::TestInDomain::test_filtered_result_should_be_ndarray_not_tuple XFAILs: `xs, ys = lzip(*filtered)` unzips a list of (x, y) pairs into two tuples-of- scalars. This happens whenever a domain is set and at least one point passes the filter (i.e., essentially always for realistic calls), not just when some points get excluded.) [ 28%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::TestInDomain::test_no_domain_returns_input_unchanged PASSED [ 28%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_l2norm_shortcut_matches_numerical_integration[Triangular] PASSED [ 28%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_kernel_var_shortcut_matches_numerical_integration[Biweight] PASSED [ 28%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_uniform_hardcoded_constants_match_closed_form PASSED [ 28%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_l2norm_shortcut_matches_numerical_integration[Gaussian] PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_normal_reference_constant_requires_second_order PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_call_is_alias_for_shape PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_density_var_and_confint PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_customkernel_h_property PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_kernel_var_shortcut_matches_numerical_integration[Epanechnikov] PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_l2norm_shortcut_matches_numerical_integration[Epanechnikov] PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_uniform_shape_does_not_accept_scalar_input XFAILs x to be array-like (it calls x.shape), so it raises AttributeError for a plain scalar float input -- exactly what scipy.integrate.quad (used internally by the lazy L2Norm/kernel_var/norm_const properties) always passes. This is normally masked because Uniform.__init__ hardcodes _L2Norm, _kernel_var, and norm=1.0, so those lazy properties are never actually computed in practice -- but calling _shape directly with a scalar, as any generic CustomKernel-consuming code might reasonably do, fails.) [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_kernel_var_shortcut_matches_numerical_integration[Gaussian] PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_customkernel_requires_callable_shape PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_weight_is_normconst_times_shape PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_moments PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_l2norm_shortcut_matches_numerical_integration[Biweight] PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_kernel_var_shortcut_matches_numerical_integration[Triangular] PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::test_cosine2_matches_stata_definition_at_zero PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::TestNdKernel::test_density_with_weights XFAILs * weights) / sum(weights)`, but np.mean already divides by n, so this divides by n a second time via sum(weights) -- the correct weighted-mean formula is np.sum(kernel_vals * weights) / sum(weights) (no extra np.mean). For uniform weights=np.ones(n), sum(weights)==n, so the result is off from the correct (and from the unweighted-branch) answer by a factor of n.) [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::TestNdKernel::test_density_with_weights_matches_correct_weighted_mean_formula PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::TestNdKernel::test_density_returns_nan_for_empty_input PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::TestNdKernel::test_default_construction_uses_gaussian_and_identity_h PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::TestNdKernel::test_density_is_finite_and_matches_call PASSED [ 29%] statsmodels/sandbox/nonparametric/tests/test_kernels.py::TestNdKernel::test_h_property_getter_setter PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion[mom7] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion_types[mnc2mc] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion[mom6] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion_types[mvsk2mnc] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion[mom4] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion[mom5] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion_types[mc2mnc] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion_types[mnc2cum] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_cov2corr PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion[mom0] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion_types[mc2cum] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion[mom1] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion[mom3] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion_types[mc2mvsk] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion[mom2] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion[mom8] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion_types[cum2mc] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion[mom9] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_multidimensional[test_vals1] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_mnc2mvsk_standard_normal PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_multidimensional[test_vals0] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion_types[mvsk2mc] PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_mnc2mvsk_exponential PASSED [ 29%] statsmodels/stats/tests/test_moment_helpers.py::test_moment_conversion[mom10] PASSED [ 29%] statsmodels/tools/tests/test_data.py::test_missing_data_pandas PASSED [ 29%] statsmodels/tools/tests/test_data.py::test_formula_engine_use_detection_577 PASSED [ 29%] statsmodels/tools/tests/test_data.py::test_dataframe PASSED [ 29%] statsmodels/tools/tests/test_data.py::test_as_array_with_name_array PASSED [ 29%] statsmodels/tools/tests/test_data.py::test_as_array_with_name_series PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_filter2 XFAIL (BUG: filter2() does `from statsmodels.tsa.filters import fftconvolve3`, but fftconvolve3 is not (no longer?) re-exported from that package's __init__ -- it now only lives in statsmodels.tsa.filters.filtertools. filter2() always raises ImportError. Separately, even fftconvolve3 itself currently raises AttributeError on modern numpy (`np.complex` was removed as a deprecated alias), so fixing the import alone would not be enough to make filter2() work.) [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_spdmapoly_with_default_w XFAILNone:` branch, but `nfreq` is not a parameter, local, or module-level name anywhere -- calling spdmapoly(None) always raises NameError.) [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_spd_shape_is_2n PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_spdar1_scalar_and_array_ar_are_consistent PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_filter_matches_direct_fft_ratio PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_pad_extends_both_polynomials PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_spdshift_shape_and_nonnegative PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_fftarma_default_n_is_nobs PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_spdpoly_approximates_spdroots PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_acf2spdfreq_shape PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_fftma_default_length_should_match_ma_not_ar XFAILnomial to the *AR* polynomial's length by default -- almost certainly copy-pasted from fftar() without updating self.ar to self.ma. Whenever len(ar) != len(ma), fftma(None) returns an array of the wrong length (matching ar, not ma).) [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_filter_n_equals_fftarma_branch_is_unreachable PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_fftma_explicit_length PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_fftarma_equals_fftma_over_fftar PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_invpowerspd_matches_inherited_acovf PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_padarr_atstart PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_padarr_atend PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_spddirect_is_nonnegative PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_spdroots_matches_closed_form_ar1_formula PASSED [ 29%] statsmodels/sandbox/tsa/tests/test_fftarma.py::test_fftar_default_length_matches_ar PASSED [ 29%] statsmodels/tools/tests/test_rng_qrng.py::test_generator_instance_passthrough PASSED [ 29%] 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PASSED [ 37%] statsmodels/tsa/tests/test_adfvalues.py::test_mackinnonp_valid_regression[ctt] PASSED [ 37%] statsmodels/tsa/tests/test_adfvalues.py::test_mackinnoncrit_invalid_regression_raises PASSED [ 37%] statsmodels/tsa/tests/test_adfvalues.py::test_mackinnonp_valid_regression[n] PASSED [ 37%] statsmodels/tsa/tests/test_adfvalues.py::test_mackinnonp_invalid_regression_raises PASSED [ 37%] statsmodels/tsa/tests/test_adfvalues.py::test_mackinnoncrit_valid_regression[n] PASSED [ 37%] statsmodels/tsa/tests/test_adfvalues.py::test_mackinnoncrit_valid_regression[ctt] PASSED [ 37%] statsmodels/tsa/tests/test_adfvalues.py::test_mackinnonp_valid_regression[ct] PASSED [ 37%] statsmodels/tsa/tests/test_adfvalues.py::test_mackinnoncrit_valid_regression[ct] PASSED [ 37%] statsmodels/tsa/tests/test_adfvalues.py::test_mackinnoncrit_valid_regression[c] PASSED [ 37%] statsmodels/tsa/tests/test_adfvalues.py::test_mackinnonp_valid_regression[c] PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::TestMedianTestKsample::test_statistic_matches_scipy PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::TestMedianTestKsample::test_pvalue_matches_scipy XFAIL.ravel(), expected.ravel(), ddof=1) call. For a (2, ngroups) contingency table, the correct degrees of freedom is (2-1)*(ngroups-1) = ngroups-1, which requires ddof=ngroups (since chisquare's dof = ncells-1-ddof and ncells=2*ngroups here), not the hardcoded 1. The reported chi-square statistic matches scipy.stats.median_test exactly (see test_statistic_matches_scipy), but with the wrong ddof the p-value does not -- e.g., for this dataset the sandbox version reports p=0.300 where the correct value (matching scipy.stats.median_test) is p=0.087.) [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::TestMedianTestKsample::test_pvalue_matches_scipy_with_correct_ddof PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::TestTotalRunsProb::test_cdf_at_max_is_one PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::TestTotalRunsProb::test_cdf_matches_cumulative_pdf PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::TestTotalRunsProb::test_pdf_sums_to_one_over_full_support PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_invalid_string_cutoff_raises PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_mean_cutoff PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_median_cutoff PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_single_run PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_numeric_cutoff PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_runstest_2samp_requires_y_or_groups PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_runstest_2samp_no_ties PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_runstest_2samp_with_groups_argument PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_runstest_2samp_wrong_number_of_groups_raises PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_runstest_2samp_with_ties_integer_input_raises XFAILps == gruni[0]] += eps` where eps is a float. If the input arrays are integer-dtyped (a reasonable thing to pass for count/discrete data, which is exactly when ties are most likely), `xx` is also integer-dtyped and the in-place += with a float eps raises UFuncTypeError under numpy's same_kind casting rule. The same call with float-dtyped input (otherwise identical) works fine, see test_runstest_2samp_with_ties.) [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_runstest_2samp_with_ties PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_runsprob_pdf_matches_reference_values PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_symmetry_bowker_asymmetric_table_matches_manual_formula PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_symmetry_bowker_symmetric_table_gives_zero_statistic PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_symmetry_bowker_requires_square_table PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_cochrans_q_matches_current_implementation PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::test_mcnemar_from_table_wrong_shape_raises PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::TestRunsClass::test_runs_test_matches_runstest_1samp PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::TestRunsClass::test_basic_attributes PASSED [ 37%] statsmodels/sandbox/stats/tests/test_runs.py::TestRunsClass::test_all_same_value_is_single_run PASSED [ 37%] statsmodels/multivariate/tests/test_factor.py::test_no_endog_no_corr_raises PASSED [ 37%] statsmodels/multivariate/tests/test_factor.py::test_getframe_smoke PASSED [ 37%] statsmodels/multivariate/tests/test_factor.py::test_factor_scoring PASSED [ 37%] statsmodels/multivariate/tests/test_factor.py::test_auto_col_name PASSED [ 37%] statsmodels/multivariate/tests/test_factor.py::test_example_compare_to_R_output PASSED [ 37%] statsmodels/multivariate/tests/test_factor.py::test_direct_corr_matrix PASSED [ 37%] statsmodels/multivariate/tests/test_factor.py::test_unknown_fa_method_error PASSED [ 37%] statsmodels/multivariate/tests/test_factor.py::test_plots PASSED [ 37%] statsmodels/multivariate/tests/test_factor.py::test_both_endog_and_corr_warns PASSED [ 37%] statsmodels/multivariate/tests/test_factor.py::test_factor_missing PASSED [ 37%] statsmodels/base/tests/test_penalties.py::TestSmoothedSCAD::test_derivatives PASSED [ 37%] statsmodels/base/tests/test_penalties.py::TestSmoothedSCAD::test_symmetry PASSED [ 37%] statsmodels/base/tests/test_penalties.py::TestPseudoHuber::test_backward_compatibility PASSED [ 37%] statsmodels/base/tests/test_penalties.py::TestPseudoHuber::test_derivatives PASSED [ 37%] statsmodels/base/tests/test_penalties.py::TestPseudoHuber::test_deprecated_priority PASSED [ 37%] statsmodels/base/tests/test_penalties.py::TestPseudoHuber::test_weights_assignment PASSED [ 37%] statsmodels/base/tests/test_penalties.py::TestPseudoHuber::test_symmetry PASSED [ 37%] statsmodels/base/tests/test_penalties.py::TestL2Constraints1::test_symmetry PASSED [ 37%] statsmodels/base/tests/test_penalties.py::TestL2Constraints1::test_derivatives PASSED [ 37%] statsmodels/base/tests/test_penalties.py::TestL2Constraints1::test_values PASSED [ 37%] statsmodels/base/tests/test_penalties.py::TestL2::test_symmetry PASSED [ 37%] 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statsmodels/tsa/arima/tests/test_model.py::test_reproducible_simulation[default_rng] PASSED [ 37%] statsmodels/tsa/arima/tests/test_model.py::test_hannan_rissanen PASSED [ 37%] statsmodels/tsa/arima/tests/test_model.py::test_cov_type_none PASSED [ 37%] statsmodels/tsa/arima/tests/test_model.py::test_yule_walker PASSED [ 37%] statsmodels/tsa/arima/tests/test_model.py::test_append_with_exog PASSED [ 37%] statsmodels/tsa/arima/tests/test_model.py::test_append_with_exog_pandas PASSED [ 37%] statsmodels/tsa/arima/tests/test_model.py::test_append PASSED [ 37%] statsmodels/tsa/arima/tests/test_model.py::test_burg PASSED [ 37%] statsmodels/tsa/arima/tests/test_model.py::test_append_with_exog_and_trend PASSED [ 37%] statsmodels/tsa/arima/tests/test_model.py::test_reproducible_simulation[7] PASSED [ 37%] statsmodels/tsa/arima/tests/test_model.py::test_hannan_rissanen_with_fixed_params[ar_order3-0-fixed_params3] PASSED [ 37%] statsmodels/tsa/arima/tests/test_model.py::test_innovations PASSED [ 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statsmodels/multivariate/tests/test_multivariate_ols.py::test_invalid_fit_method_raises[MultivariateLS] PASSED [ 37%] statsmodels/multivariate/tests/test_multivariate_ols.py::test_exog_1D_array[_MultivariateOLS] PASSED [ 37%] statsmodels/multivariate/tests/test_multivariate_ols.py::test_from_formula_vs_no_formula[_MultivariateOLS] PASSED [ 37%] statsmodels/multivariate/tests/test_multivariate_ols.py::test_glm_dogs_example[MultivariateLS] PASSED [ 37%] statsmodels/multivariate/tests/test_multivariate_ols.py::test_specify_L_M_by_string[MultivariateLS] PASSED [ 37%] statsmodels/multivariate/tests/test_multivariate_ols.py::test_specify_L_M_by_string[_MultivariateOLS] PASSED [ 37%] statsmodels/multivariate/tests/test_multivariate_ols.py::test_endog_1D_array PASSED [ 37%] statsmodels/multivariate/tests/test_multivariate_ols.py::test_resid_distance_and_hat_matrix_diag PASSED [ 37%] statsmodels/multivariate/tests/test_multivariate_ols.py::test_multivariate_ls_results_summary PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestACF_FFT::test_qstat PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestACF_FFT::test_acf PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestACFMissing::test_qstat_conservative PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestACFMissing::test_drop_all[drop] PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestACFMissing::test_qstat_drop PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestACFMissing::test_acf_conservative PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestACFMissing::test_qstat_none PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestACFMissing::test_drop_all[conservative] PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestACFMissing::test_confint_conservative PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestACFMissing::test_raise PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestACFMissing::test_confint_drop PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestACFMissing::test_acf_drop PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestACFMissing::test_acf_none PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestADFConstant2::test_pvalue PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestADFConstant2::test_teststat PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestADFConstant2::test_critvalues PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestCoint_t::test_tstat PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestKPSS::test_kpss_fails_on_nobs_check PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestKPSS::test_result_object_default_warns PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestKPSS::test_pval PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestKPSS::test_teststat PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::TestKPSS::test_unknown_lags PASSED [ 37%] 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statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[True-False-True-raise] PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-False-True-conservative] PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_adfuller_result_object_matches_legacy_values PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_innovations_algo_rtol PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-True-True-conservative] PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_adfuller_result_object_true_without_autolag PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_acovf_fft_vs_convolution[False-True] PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_diebold_mariano_exceptions PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_acovf2d PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-True-False-none] PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_compare_acovf_vs_ccovf[True-True-False] PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_innovations_algo_brockwell_davis PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[True-True-False-drop] PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_ccovf_adjusted_shorter_y[False] PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_pacf2acf_errors PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[False-True-False-conservative] PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_ccovf_different_lengths[True-True] PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_ccovf_different_lengths[False-True] PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_ccovf_fft_vs_convolution[True-True] PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-False-False-conservative] PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_adfuller_result_object_true_returns_result_object PASSED [ 37%] statsmodels/tsa/tests/test_stattools.py::test_ccovf_different_lengths[False-False] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[False-True-True-conservative] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[True-False-False-conservative] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_ccovf_different_lengths_known_lag PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[True-True-True-drop] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_ccovf_fft_vs_convolution[False-False] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_pacf2acf_ar PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[True-False-False-raise] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_adfuller_maxlag_too_large PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[True-True-True-raise] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-True-True-none] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[True-True-False-conservative] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_fft_vs_convolution[True-False] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[True-True-False-drop] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_levinson_durbin_acov PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_innovations_filter_brockwell_davis PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-False-False-raise] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_ccovf_different_lengths[True-False] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[True-False-False-drop] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-False-False-none] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_compare_acovf_vs_ccovf[True-False-True] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acf_fft_dataframe PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_fft_vs_convolution[True-True] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_adfuller_result_object_default_warns PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[True-True-False-conservative] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[True-False-True-none] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[False-True-False-drop] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-False-True-drop] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[True-True-True-conservative] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_pacf2acf_levinson_durbin PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[True-False-False-conservative] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_adfuller_result_object_true_with_store PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_ccf_different_lengths PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-True-True-drop] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[False-False-False-conservative] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_innovations_filter_pandas PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[True-True-True-none] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_innovations_filter_errors PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_adfuller_short_series PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-True-True-raise] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-True-False-conservative] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_fft_vs_convolution[False-False] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_error PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_ccovf_fft_vs_convolution[True-False] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[True-True-True-drop] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-False-True-none] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[True-False-True-drop] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_compare_acovf_vs_ccovf[False-False-False] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-False-False-drop] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_diebold_mariano_callable_smoke PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[True-False-False-none] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_compare_acovf_vs_ccovf[False-True-False] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_compare_acovf_vs_ccovf[True-False-False] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[False-False-True-conservative] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[True-False-True-conservative] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_compare_acovf_vs_ccovf[True-True-True] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_diebold_mariano_test PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-False-True-raise] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[True-False-True-drop] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-True-False-raise] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_ccovf_adjusted_shorter_y[True] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_innovations_errors PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_pandasacovf PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_diebold_mariano_harvey_adj PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_arma_order_select_ic PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_diebold_mariano_equiv PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[True-False-True-conservative] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_innovations_algo_filter_kalman_filter PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[True-True-True-conservative] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[True-False-False-drop] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_ccovf_fft_vs_convolution[False-True] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_compare_acovf_vs_ccovf[False-True-True] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_adfuller_result_object_false_silences_warning PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[False-True-True-drop] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[True-True-False-none] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_arma_order_select_ic_failure PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[False-False-True-drop] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags[False-True-False-drop] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_compare_acovf_vs_ccovf[False-False-True] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_nlags_missing[False-False-False-drop] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_coint_auto_tstat PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_pacf_small_sample[3] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_granger_causality_exception_maxlag PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_pacf_small_sample[7] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_pacf_1_obs PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_pacf_small_sample[5] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acf_conservate_nanops PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_zivot_andrews_change_data PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_pacf_small_sample[9] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_granger_causality_exceptions[dataset1] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_granger_causality_exceptions[dataset0] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_pacf_nlags_error PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_granger_causality_exceptions[dataset2] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_granger_causality_exceptions[dataset3] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_acovf_all_missing PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::test_stattools_fixed_arity_result_objects PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestADFNoConstant2::test_pvalue PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestADFNoConstant2::test_critvalues PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestADFNoConstant2::test_store_str PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestADFNoConstant2::test_teststat PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestADFConstantTrend2::test_critvalues PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestADFConstantTrend2::test_teststat PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestADFConstantTrend2::test_pvalue PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_confint_widths PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_pccf_edge_cases PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_alpha_default_returns_result_object PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_constant_series[ywm] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_no_alpha_never_warns PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_confint PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_independent_series PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_pccf_parameter_validation PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_var1_pccf_cutoff PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_yw_method_aliases PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_pccf PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_inf_input_raises PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_yw_analytical_var1 PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_constant_series[ols] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_yw_ols_agreement_stationary PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_default_nlags PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_return_consistency PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_nan_fallback_large_lag PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_ols_underdetermined_returns_nan PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_pccf_hand_computed PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_alpha_result_object_true PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_pccf_statistical_properties PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_nan_input_raises PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_yw_singular_intermediate_recursion_returns_nan PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_method_parameter_validation PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_constant_series[yw] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPCCF::test_asymmetry PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestGrangerCausality::test_granger_fails_on_finite_check PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestGrangerCausality::test_granger_fails_on_zero_lag PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestGrangerCausality::test_grangercausality PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestGrangerCausality::test_grangercausality_single PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestGrangerCausality::test_granger_fails_on_nobs_check PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPACF::test_ld PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPACF::test_ols PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPACF::test_ols_inefficient PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPACF::test_no_alpha_never_warns PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPACF::test_burg PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPACF::test_alpha_result_object_true PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPACF::test_yw PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPACF::test_alpha_default_returns_result_object PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestPACF::test_yw_singular PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_alternative[two-sided-41-0.047619047619047616] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_1d_input PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_alternative_deprecated_alias[i-increasing] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_use_chi2 PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_unbalanced_degrees_of_freedom[increasing-False] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_unbalanced_degrees_of_freedom[increasing-True] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_subset_length[2-41-0.047619047619047616] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_alternative[decreasing-0.024390243902439025-0.9761904761904762] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_subset_length[0.5-10-0.09048484886749095] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_unbalanced_degrees_of_freedom[two-sided-False] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_alternative[increasing-41-0.023809523809523808] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_alternative_deprecated_alias[d-decreasing] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_unbalanced_degrees_of_freedom[decreasing-False] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_one_sided_alternatives_are_complementary[balanced] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_alternative_deprecated_alias[2-two-sided] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_one_sided_alternatives_are_complementary[unbalanced] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_unbalanced_degrees_of_freedom[two-sided-True] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_2d_input_with_missing_values PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_unbalanced_degrees_of_freedom[decreasing-True] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestADFConstantTrend::test_critvalues PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestADFConstantTrend::test_pvalue PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestADFConstantTrend::test_teststat PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestADFConstant::test_teststat PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestADFConstant::test_critvalues PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestADFConstant::test_pvalue PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestACF::test_legacy_unpacking_preserved[kwargs2-4] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestACF::test_default_warns PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestACF::test_qstat PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestACF::test_legacy_unpacking_preserved[kwargs1-3] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestACF::test_acf PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestACF::test_result_object_true PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestACF::test_result_object_true_always_four_fields[None-True] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestACF::test_no_qstat_no_alpha_never_warns PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestACF::test_confint PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestACF::test_result_object_true_always_four_fields[0.05-False] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestACF::test_result_object_true_always_four_fields[0.05-True] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestACF::test_result_object_true_always_four_fields[None-False] SKIPPED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestACF::test_only_full_request_adopts_result_object_silently PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestACF::test_legacy_unpacking_preserved[kwargs0-2] PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBlockJackknife::test_non_callable_statistic PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBlockJackknife::test_acf_runs PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBlockJackknife::test_hand_computed PASSED [ 38%] statsmodels/tsa/tests/test_stattools.py::TestBlockJackknife::test_mean_closed_form PASSED [ 38%] 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statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-approximate_diffuse-all-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-stationary-all-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-diffuse-None-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-diffuse-all-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-stationary-None-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-approximate_diffuse-None-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-diffuse-init-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_dynamic_factor[periods2-all] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-diffuse-init-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-diffuse-init-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-stationary-mixed-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-approximate_diffuse-init-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-approximate_diffuse-mixed-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[False-periods2-mixed] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-approximate_diffuse-all-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-approximate_diffuse-init-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-stationary-init-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-approximate_diffuse-None-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[True-0-all] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-diffuse-all-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-diffuse-init-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-stationary-mixed-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-approximate_diffuse-mixed-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-diffuse-mixed-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-diffuse-mixed-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-stationary-all-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-approximate_diffuse-init-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[True-periods1-init] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[False-periods2-all] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-approximate_diffuse-mixed-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-approximate_diffuse-init-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-approximate_diffuse-all-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-diffuse-all-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-stationary-mixed-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-stationary-None-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-approximate_diffuse-all-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[False-0-None] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-approximate_diffuse-init-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_varmax[periods1-None] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-stationary-mixed-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-diffuse-mixed-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-diffuse-mixed-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-stationary-mixed-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-diffuse-init-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-approximate_diffuse-mixed-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-diffuse-all-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-approximate_diffuse-init-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-diffuse-None-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-approximate_diffuse-None-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-diffuse-mixed-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-diffuse-mixed-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-stationary-mixed-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_varmax[0-mixed] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[False-periods2-None] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[True-periods1-mixed] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[True-0-mixed] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[True-periods2-all] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[True-periods2-init] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-stationary-None-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-stationary-mixed-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-stationary-all-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-approximate_diffuse-init-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-diffuse-init-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-approximate_diffuse-mixed-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-approximate_diffuse-all-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_simulation_smoothing[mixed] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-approximate_diffuse-None-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[False-periods1-None] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_varmax[0-None] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_basic[init] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-stationary-init-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-stationary-mixed-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_dynamic_factor[periods1-None] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-approximate_diffuse-mixed-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-diffuse-None-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-stationary-mixed-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-diffuse-mixed-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-diffuse-mixed-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[True-0-init] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[False-periods1-mixed] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-diffuse-None-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[True-0-init] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-diffuse-all-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-approximate_diffuse-mixed-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-approximate_diffuse-None-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[True-periods1-all] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[False-0-init] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-approximate_diffuse-mixed-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-diffuse-mixed-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-stationary-mixed-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-diffuse-init-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-stationary-init-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-diffuse-init-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[True-periods1-mixed] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-approximate_diffuse-init-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-approximate_diffuse-None-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-stationary-all-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-approximate_diffuse-init-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[False-periods2-None] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-approximate_diffuse-all-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-stationary-all-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-diffuse-init-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-stationary-mixed-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_dynamic_factor[periods2-None] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-diffuse-all-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_dynamic_factor[0-init] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-approximate_diffuse-init-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-stationary-init-True] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_varmax[0-all] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-approximate_diffuse-init-False] PASSED [ 40%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-stationary-mixed-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-diffuse-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-approximate_diffuse-all-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-stationary-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-approximate_diffuse-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-stationary-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[False-periods1-None] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[False-0-mixed] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-diffuse-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-stationary-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-approximate_diffuse-mixed-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-diffuse-init-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-stationary-init-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-diffuse-init-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-stationary-all-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-approximate_diffuse-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[True-periods1-init] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[False-periods2-all] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-stationary-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_simulation_smoothing[None] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-stationary-init-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-stationary-all-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-approximate_diffuse-mixed-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-diffuse-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_varmax[periods2-mixed] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-diffuse-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_time_varying_model PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-stationary-init-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-diffuse-init-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-diffuse-mixed-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-approximate_diffuse-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_dynamic_factor[0-all] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-diffuse-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-diffuse-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[False-periods1-mixed] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-stationary-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-diffuse-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-diffuse-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-stationary-mixed-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_varmax[periods2-all] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-stationary-mixed-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-approximate_diffuse-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-stationary-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_varmax[periods2-init] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-stationary-init-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-diffuse-mixed-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-approximate_diffuse-all-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-diffuse-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-diffuse-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-diffuse-all-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-diffuse-all-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[True-periods2-None] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_dynamic_factor[periods1-all] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-diffuse-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_dynamic_factor[periods1-mixed] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-stationary-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-approximate_diffuse-mixed-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-stationary-init-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-stationary-all-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-approximate_diffuse-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-approximate_diffuse-all-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-diffuse-all-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-stationary-all-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_varmax[periods1-init] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-approximate_diffuse-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-diffuse-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-approximate_diffuse-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-stationary-init-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-approximate_diffuse-init-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[False-0-init] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-stationary-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-diffuse-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-approximate_diffuse-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-stationary-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-approximate_diffuse-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[True-periods1-None] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-approximate_diffuse-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-diffuse-mixed-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-stationary-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-stationary-mixed-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-diffuse-mixed-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[False-0-mixed] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[True-0-mixed] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-diffuse-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[False-0-all] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[False-periods1-all] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-approximate_diffuse-mixed-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-approximate_diffuse-init-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-approximate_diffuse-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[False-0-all] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-approximate_diffuse-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-approximate_diffuse-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[False-0-None] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-stationary-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-approximate_diffuse-init-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-approximate_diffuse-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-diffuse-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-stationary-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[True-0-None] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-approximate_diffuse-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_dynamic_factor[periods1-init] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_dynamic_factor[0-mixed] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[True-0-None] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[True-periods2-mixed] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-diffuse-init-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[True-periods1-all] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-stationary-mixed-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_basic[None] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_varmax[0-init] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[False-periods1-init] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-diffuse-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-stationary-all-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-approximate_diffuse-all-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[True-periods2-None] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-approximate_diffuse-mixed-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-stationary-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[False-periods2-mixed] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-approximate_diffuse-init-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-diffuse-init-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[True-periods2-all] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-stationary-init-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-approximate_diffuse-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-approximate_diffuse-mixed-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-approximate_diffuse-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[False-periods2-init] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[True-0-all] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods1-stationary-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-stationary-init-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-diffuse-mixed-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-stationary-init-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-diffuse-init-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods1-diffuse-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-approximate_diffuse-init-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-stationary-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-diffuse-init-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-diffuse-mixed-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-stationary-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[True-periods1-None] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-stationary-mixed-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-0-stationary-all-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-approximate_diffuse-init-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_unobserved_components[False-periods1-init] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[True-periods2-mixed] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-stationary-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[0-approximate_diffuse-mixed-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-stationary-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods2-diffuse-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-diffuse-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[None-periods2-approximate_diffuse-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-diffuse-all-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_basic[mixed] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-diffuse-None-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_dynamic_factor[periods2-init] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-periods1-stationary-init-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-stationary-all-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_dynamic_factor[0-None] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_smoother_output[alternate_timing-0-diffuse-mixed-True] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[False-periods1-all] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_filter_output[periods2-approximate_diffuse-None-False] PASSED [ 41%] statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py::test_sarimax[False-periods2-init] PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_pandas2d PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_pandas PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_odd_length_filter PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_recursive PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_convolution2d PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_convolution PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_hpfilter_pandas PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_bking_pandas PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_cffilter_returns_cycletrendresult PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_hpfilter PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_bking2d PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_cfitz_pandas PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_bking1d PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_cfitz_filter PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_hpfilter_returns_cycletrendresult PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_miso_lfilter_combines_inputs_like_a_causal_fir_filter[3] PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_miso_lfilter_combines_inputs_like_a_causal_fir_filter[2] PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_fftconvolve3_modes[full] PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_miso_lfilter_combines_inputs_like_a_causal_fir_filter[1] PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_miso_lfilter_combines_inputs_like_a_causal_fir_filter[4] PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_fftconvolve3_complex_dtype PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_fftconvolve3_matches_lfilter PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_miso_lfilter_combines_inputs_like_a_causal_fir_filter[5] PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_fftconvolve3_modes[same] PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_fftconvolve3_modes[valid] PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_pandas_freq_decorator PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_miso_lfilter_applies_ar_dynamics_to_combined_input PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_fftconvolveinv_roundtrip PASSED [ 41%] statsmodels/tsa/filters/tests/test_filters.py::test_miso_lfilter_useic_zero_matches_default PASSED [ 41%] statsmodels/sandbox/distributions/tests/test_transf.py::Test_Transf2::test_equivalent_negsq PASSED [ 41%] statsmodels/sandbox/distributions/tests/test_transf.py::Test_Transf2::test_equivalent PASSED [ 41%] statsmodels/graphics/tests/test_correlation.py::test_plot_corr PASSED [ 41%] statsmodels/graphics/tests/test_correlation.py::test_plot_corr_grid PASSED [ 41%] statsmodels/tools/tests/test_testing.py::test_assert_equal_index_forwards_kwds PASSED [ 41%] statsmodels/tools/tests/test_testing.py::test_assert_equal_forwards_err_msg PASSED [ 41%] statsmodels/tools/tests/test_testing.py::test_bad_table PASSED [ 41%] statsmodels/tools/tests/test_testing.py::test_holder PASSED [ 41%] statsmodels/stats/tests/test_multivariate.py::TestCovStructure::test_spherical PASSED [ 41%] statsmodels/stats/tests/test_multivariate.py::TestCovStructure::test_covmat PASSED [ 41%] statsmodels/stats/tests/test_multivariate.py::TestCovStructure::test_blockdiagonal PASSED [ 41%] statsmodels/stats/tests/test_multivariate.py::TestCovStructure::test_diagonal PASSED [ 41%] statsmodels/stats/tests/test_multivariate.py::test_mv_mean PASSED [ 41%] statsmodels/stats/tests/test_multivariate.py::test_mvmean_2indep PASSED [ 41%] statsmodels/stats/tests/test_multivariate.py::test_confint_simult PASSED [ 41%] statsmodels/stats/tests/test_multivariate.py::test_cov_oneway PASSED [ 41%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsUnit::test_kernels_vectorized[case0] PASSED [ 41%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsUnit::test_kernels_vectorized[case1] PASSED [ 41%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsUnit::test_kernels[case1] PASSED [ 41%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsUnit::test_kernels_weights[case1] PASSED [ 41%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsUnit::test_kernels_weights[case0] PASSED [ 41%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsUnit::test_kernels[case0] PASSED [ 41%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case0] PASSED [ 41%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_vectorized[case1] PASSED [ 41%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case1] PASSED [ 41%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_vectorized[case0] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case3] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_vectorized[case2] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case2] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_vectorized[case3] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_vectorized[case6] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case7] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_vectorized[case7] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case6] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_vectorized[case5] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case4] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_vectorized[case4] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case5] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels[case2] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels[case3] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels[case1] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels[case0] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels[case5] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels[case4] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels[case6] PASSED [ 42%] statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels[case7] PASSED [ 42%] statsmodels/base/tests/test_predict.py::TestPredictGLM::test_without_formula PASSED [ 42%] statsmodels/base/tests/test_predict.py::TestPredictGLM::test_2d PASSED [ 42%] statsmodels/base/tests/test_predict.py::TestPredictGLM::test_1d PASSED [ 42%] statsmodels/base/tests/test_predict.py::TestPredictGLM::test_predict_offset PASSED [ 42%] statsmodels/base/tests/test_predict.py::TestPredictOLS::test_1d PASSED [ 42%] statsmodels/base/tests/test_predict.py::TestPredictOLS::test_2d PASSED [ 42%] statsmodels/base/tests/test_predict.py::TestPredictOLS::test_without_formula PASSED [ 42%] statsmodels/sandbox/stats/tests/test_multicomp.py::test_tukey_pvalues SKIPPED [ 42%] statsmodels/sandbox/stats/tests/test_multicomp.py::test_get_tukeyqcrit_invalid_alpha_raises PASSED [ 42%] statsmodels/sandbox/stats/tests/test_multicomp.py::test_tiecorrect_matches_scipy PASSED [ 42%] statsmodels/sandbox/stats/tests/test_multicomp.py::test_get_tukeyqcrit_matches_published_table PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_matrices_somewhat_complicated_model PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_predict_custom_index PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_local_level PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_random_walk_with_drift PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_deterministic_trend PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_random_trend PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_forecast PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_plot_components_invalid_which_raises PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_rtrend_ar1 PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_summary_after_remove_data PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_random_walk PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_reg PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_forecast_exog PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_local_linear_trend PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_specifications PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_misc_exog PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_smooth_trend PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_freq_seasonal PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_local_linear_deterministic_trend PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_start_params PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_irregular PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_cycle PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_append_results PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_fixed_slope_warn PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_fixed_slope PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_mle_reg[True] PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_deterministic_constant PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_lltrend_cycle_seasonal_reg_ar1 PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_fixed_intercept PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_recreate_model PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_mle_reg[False] PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_apply_results PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_extend_results PASSED [ 42%] statsmodels/tsa/statespace/tests/test_structural.py::test_seasonal PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestCLogLogModel::test_pandas PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestCLogLogModel::test_formula PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestCLogLogModel::test_basic PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestCLogLogModel::test_unordered PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestCLogLogModel::test_results_other PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestProbitModel::test_formula_eval_env PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestProbitModel::test_formula PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestProbitModel::test_formula_categorical PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestProbitModel::test_basic PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestProbitModel::test_loglikerelated PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestProbitModel::test_pandas PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestProbitModel::test_results_other PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestProbitModel::test_offset PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestProbitModel::test_unordered PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestLogitModel::test_results_other PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestLogitModel::test_basic PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestLogitModel::test_formula PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestLogitModel::test_postestimation PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestLogitModel::test_pandas PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestLogitModel::test_unordered PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::test_summary_after_remove_data PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::test_nan_endog_exceptions PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::test_predict_which PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestLogitBinary::test_attributes PASSED [ 42%] statsmodels/miscmodels/tests/test_ordinal_model.py::TestLogitModelFormula::test_setup PASSED [ 42%] statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_brockwell_davis_example_511 PASSED [ 42%] statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_misc PASSED [ 42%] statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_invalid PASSED [ 42%] statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_nonstationary_series_variance XFAIL [ 42%] statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_nonstationary_series PASSED [ 42%] statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_itsmr PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMultipleEqsDataFrames::test_labels PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMultipleEqsDataFrames::test_orig PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMultipleEqsDataFrames::test_names PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMultipleEqsDataFrames::test_attach PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMultipleEqsDataFrames::test_endogexog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFrameArray::test_attach PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFrameArray::test_endogexog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFrameArray::test_labels PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFrameArray::test_orig PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFrameArray::test_names PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFrames::test_labels PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFrames::test_orig PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFrames::test_names PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFrames::test_endogexog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFrames::test_attach PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrays::test_endogexog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrays::test_names PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrays::test_attach PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrays::test_labels PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrays::test_orig PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFramesWithMultiIndex::test_attach PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFramesWithMultiIndex::test_orig PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFramesWithMultiIndex::test_labels PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFramesWithMultiIndex::test_names PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFramesWithMultiIndex::test_endogexog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestHasConstantGLM::test_hasconst PASSED [ 42%] statsmodels/base/tests/test_data.py::TestHandleMissing::test_noop PASSED [ 42%] statsmodels/base/tests/test_data.py::TestHandleMissing::test_array_pandas PASSED [ 42%] statsmodels/base/tests/test_data.py::TestHandleMissing::test_pandas_array PASSED [ 42%] statsmodels/base/tests/test_data.py::TestHandleMissing::test_arrays PASSED [ 42%] statsmodels/base/tests/test_data.py::TestHandleMissing::test_pandas PASSED [ 42%] statsmodels/base/tests/test_data.py::TestLists::test_attach PASSED [ 42%] statsmodels/base/tests/test_data.py::TestLists::test_names PASSED [ 42%] statsmodels/base/tests/test_data.py::TestLists::test_orig PASSED [ 42%] statsmodels/base/tests/test_data.py::TestLists::test_labels PASSED [ 42%] statsmodels/base/tests/test_data.py::TestLists::test_endogexog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestSeriesDataFrame::test_orig PASSED [ 42%] statsmodels/base/tests/test_data.py::TestSeriesDataFrame::test_attach PASSED [ 42%] statsmodels/base/tests/test_data.py::TestSeriesDataFrame::test_endogexog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestSeriesDataFrame::test_labels PASSED [ 42%] statsmodels/base/tests/test_data.py::TestSeriesDataFrame::test_names PASSED [ 42%] statsmodels/base/tests/test_data.py::TestConstant::test_array_constant PASSED [ 42%] statsmodels/base/tests/test_data.py::TestConstant::test_pandas_noconstant PASSED [ 42%] statsmodels/base/tests/test_data.py::TestConstant::test_pandas_constant PASSED [ 42%] statsmodels/base/tests/test_data.py::TestConstant::test_array_noconstant PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrays2dEndog::test_endogexog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrays2dEndog::test_attach PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrays2dEndog::test_orig PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrays2dEndog::test_names PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrays2dEndog::test_labels PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingPandas::test_raise PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingPandas::test_labels PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingPandas::test_drop PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingPandas::test_none PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingPandas::test_endog_only_drop PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingPandas::test_mv_endog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingPandas::test_raise_no_missing PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingPandas::test_endog_only_raise PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrays1dExog::test_endogexog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrays1dExog::test_names PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrays1dExog::test_orig PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrays1dExog::test_labels PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrays1dExog::test_attach PASSED [ 42%] statsmodels/base/tests/test_data.py::TestListDataFrame::test_orig PASSED [ 42%] statsmodels/base/tests/test_data.py::TestListDataFrame::test_endogexog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestListDataFrame::test_labels PASSED [ 42%] statsmodels/base/tests/test_data.py::TestListDataFrame::test_names PASSED [ 42%] statsmodels/base/tests/test_data.py::TestListDataFrame::test_attach PASSED [ 42%] statsmodels/base/tests/test_data.py::TestHasConstantLogit::test_hasconst PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFrameList::test_labels PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFrameList::test_attach PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFrameList::test_orig PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFrameList::test_endogexog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestDataFrameList::test_names PASSED [ 42%] statsmodels/base/tests/test_data.py::test_alignment PASSED [ 42%] statsmodels/base/tests/test_data.py::test_dtype_actual_object PASSED [ 42%] statsmodels/base/tests/test_data.py::test_raise_nonfinite_exog PASSED [ 42%] statsmodels/base/tests/test_data.py::test_dtype_object PASSED [ 42%] statsmodels/base/tests/test_data.py::test_formula_missing_extra_arrays PASSED [ 42%] statsmodels/base/tests/test_data.py::TestHasConstantOLS::test_hasconst PASSED [ 42%] statsmodels/base/tests/test_data.py::TestSeriesSeries::test_attach PASSED [ 42%] statsmodels/base/tests/test_data.py::TestSeriesSeries::test_endogexog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestSeriesSeries::test_labels PASSED [ 42%] statsmodels/base/tests/test_data.py::TestSeriesSeries::test_names PASSED [ 42%] statsmodels/base/tests/test_data.py::TestSeriesSeries::test_orig PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMultipleEqsArrays::test_labels PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMultipleEqsArrays::test_attach PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMultipleEqsArrays::test_endogexog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMultipleEqsArrays::test_names PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMultipleEqsArrays::test_orig PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingArray::test_raise PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingArray::test_drop PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingArray::test_none PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingArray::test_extra_kwargs_1d PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingArray::test_endog_only_drop PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingArray::test_extra_kwargs_2d PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingArray::test_endog_only_raise PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingArray::test_mv_endog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestMissingArray::test_raise_no_missing PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrayDataFrame::test_orig PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrayDataFrame::test_endogexog PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrayDataFrame::test_labels PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrayDataFrame::test_names PASSED [ 42%] statsmodels/base/tests/test_data.py::TestArrayDataFrame::test_attach PASSED [ 42%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-exog18-2-1-3-4-1-3-12-False-True-True] PASSED [ 42%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[20-0-0-0-params13-q] PASSED [ 42%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-2-1-3-4-1-3-12-False-True-True] PASSED [ 42%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-1-0-0-params14-q] PASSED [ 42%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-2-1-3-4-1-3-12-False-False-True] PASSED [ 42%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[20-0-0-0-params4-p] PASSED [ 42%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-1-0-0-params5-p] PASSED [ 42%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-1-0-0-1-0-0-4-True-True-False] PASSED [ 42%] statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order5-seasonal_order5-True-None-None-valid5] PASSED [ 42%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-0-0-0-params11-q] PASSED [ 42%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-p10-0-q10-P10-0-Q10-4-True-True-False] PASSED [ 42%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-1-0-0-1-1-1-4-True-True-False] PASSED [ 42%] statsmodels/tsa/arima/tests/test_specification.py::test_invalid PASSED [ 42%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-1-0-1-0-0-0-0-True-True-False] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-1-1-1-0-0-0-0-True-True-False] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[y-2-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-1-0-0-params16-q] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order8-seasonal_order8-None-False-None-valid8] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[True-None-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order7-seasonal_order7-None-True-None-valid7] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-0-0-0-1-1-1-4-True-True-False] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-1-0-0-params7-p] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order4-seasonal_order4-None-None-None-valid4] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-p8-0-0-1-0-0-4-True-True-False] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[y-None-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-0-0-0-0-0-0-0-True-True-False] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order1-seasonal_order1-None-None-None-valid1] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-1-1-4-params17-q] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[True-exog21-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-2-1-3-4-1-3-12-True-False-True] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[True-2-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order0-seasonal_order0-None-None-None-valid0] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-0-0-0-params0-p] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-0-0-0-0-0-Q9-4-True-True-False] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order9-seasonal_order9-None-None-True-valid9] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-1-1-4-params8-p] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-1-0-0-0-0-0-4-True-True-False] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[2-0-0-0-params3-p] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-1-1-4-params6-p] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_misc PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order2-seasonal_order2-None-None-None-valid2] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-0-0-0-params9-q] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-2-1-3-4-1-3-12-True-True-False] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[y-exog20-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-1-1-4-params15-q] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order6-seasonal_order6-False-None-None-valid6] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[y-exog19-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-0-0-0-params2-p] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[2-0-0-0-params12-q] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_invalid_estimator PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-2-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-0-0-0-params10-q] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-0-0-0-params1-p] PASSED [ 43%] statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order3-seasonal_order3-None-None-None-valid3] PASSED [ 43%] statsmodels/stats/tests/test_sandwich.py::test_hac_simple PASSED [ 43%] statsmodels/stats/tests/test_sandwich.py::test_cov_cluster_2groups PASSED [ 43%] statsmodels/stats/tests/test_sandwich.py::test_cov_hc0_to_hc3_match_results_attributes PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_acorr_breusch_godfrey_exogs PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_het_white PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_harvey_collier PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_compare_nested[compare_j] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_pesaran_timmermann_invalid[actual0-predicted0-kwargs0-same length] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_het_breusch_pagan_1d_err PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_pesaran_timmermann_invalid[actual4-predicted4-kwargs4-alternative] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_compare_j PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_breaks_hansen PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_het_arch PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_recursive_residuals PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_acorr_ljung_box_big_default PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_het_breusch_pagan PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_acorr_ljung_box_against_r PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_pesaran_timmermann_invalid[actual1-predicted1-kwargs1-at least 2 values] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_rainbow PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_pesaran_timmermann_invalid[actual2-predicted2-kwargs2-finite] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_pesaran_timmermann_reference PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_acorr_ljung_box PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_compare_cox PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_acorr_ljung_box_small_default PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_het_white_error PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_pesaran_timmermann_store PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_compare_nested[compare_cox] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_het_goldfeldquandt PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_influence PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_normality PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_acorr_breusch_godfrey_multidim PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_pesaran_timmermann_manual_formula PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_pesaran_timmermann_invalid[actual3-predicted3-kwargs3-variance is non-positive] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_acorr_breusch_godfrey PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_cusum_ols PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_basic PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_het_white_no_interaction_terms PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_compare_lr PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_het_breusch_pagan_nonrobust PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_het_arch2 PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_compare_error[compare_j] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_hac PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticG::test_compare_error[compare_cox] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_gq PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov1-True-fitted-3] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_smoke_order_by[order_by2-0.5] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_smoke_order_by[order_by1-0.25] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_smoke_order_by[None-0.75] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_smoke_order_by[None-0.25] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_smoke_order_by[order_by1-0.75] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_het_goldfeldquandt_alternative_deprecated_alias[d-decreasing] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_encompasing_direct[nonrobust] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_diagnostics_pandas PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov1-True-fitted-2] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_smoke_order_by[order_by2-0.25] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov1-False-exog-2] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_smoke_order_by[order_by2-0.75] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_lm_test_result_object[het_arch] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov0-False-fitted-3] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov0-False-princomp-3] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_spec_white PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_use_distance_matches_manual_ordering PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov0-False-fitted-2] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_acorr_lm_smoke[cov1-2-False] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov0-False-princomp-2] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov1-False-exog-3] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_smoke_order_by[order_by4-0.25] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_smoke_order_by[order_by4-0.75] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_influence_dtype PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_acorr_lm_smoke_no_autolag PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_center_deprecated[300] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_encompasing_error PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_ljungbox_auto_lag_whitenoise PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_het_goldfeldquandt_alternative_deprecated_alias[i-increasing] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_outlier_influence_funcs PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_influence_wrapped PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov0-True-princomp-3] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov1-True-exog-2] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_acorr_lm_smoke[cov0-0-True] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov1-True-exog-3] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_use_distance_order_invariant[True] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov0-True-princomp-2] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_acorr_lm_smoke[cov1-0-False] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_small_skip PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_acorr_lm_smoke[cov1-0-True] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_smoke_order_by[None-0.5] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov1-True-princomp-3] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_het_goldfeldquandt_result_object PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov0-False-exog-3] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_smoke_order_by[order_by1-0.5] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_encompasing_direct[HC0] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_spec_white_error PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_ljungbox_dof_adj PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_het_goldfeldquandt_alternative_deprecated_alias[2-two-sided] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_acorr_lm_smoke[cov0-0-False] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov1-True-princomp-2] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_lm_test_result_object[acorr_lm] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov0-False-exog-2] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_compare_result_object_default_warns PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov0-True-fitted-3] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov1-False-fitted-3] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_outlier_test PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov1-False-fitted-2] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov0-True-fitted-2] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_ljungbox_auto_lag_selection PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_compare_result_object_true PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_exception PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_diagnostics_hac PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_smoke_order_by[order_by4-0.5] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_acorr_lm_smoke[cov0-2-False] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_center_deprecated[0.33] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov1-False-princomp-2] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_use_distance_order_invariant_discrete PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_use_distance_order_invariant[False] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_acorr_lm_smoke[cov1-2-True] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_ljungbox_period PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov0-True-exog-3] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_smoke_order_by[x0-0.75] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_linear_lm_direct PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_ljungbox_errors_warnings PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov0-True-exog-2] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_smoke_order_by[x0-0.25] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_reset_smoke[cov1-False-princomp-3] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_acorr_lm_smoke[cov0-2-True] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_lm_test_result_object[acorr_breusch_godfrey] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::test_rainbow_smoke_order_by[x0-0.5] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_acorr_breusch_godfrey PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_breaks_hansen PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_pesaran_timmermann_invalid[actual4-predicted4-kwargs4-alternative] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_pesaran_timmermann_invalid[actual0-predicted0-kwargs0-same length] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_compare_error[compare_cox] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_pesaran_timmermann_store PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_acorr_ljung_box_big_default PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_harvey_collier PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_het_white_error PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_acorr_ljung_box_small_default PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_pesaran_timmermann_reference PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_het_white PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_basic PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_compare_error[compare_j] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_compare_j PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_acorr_breusch_godfrey_exogs PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_acorr_ljung_box_against_r PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_pesaran_timmermann_manual_formula PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_het_goldfeldquandt PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_het_arch2 PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_het_breusch_pagan PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_acorr_breusch_godfrey_multidim PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_het_breusch_pagan_nonrobust PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_het_breusch_pagan_1d_err PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_hac PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_recursive_residuals PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_het_white_no_interaction_terms PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_acorr_ljung_box PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_compare_cox PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_het_arch PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_compare_nested[compare_cox] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_pesaran_timmermann_invalid[actual3-predicted3-kwargs3-variance is non-positive] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_normality PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_pesaran_timmermann_invalid[actual2-predicted2-kwargs2-finite] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_influence PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_compare_lr PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_pesaran_timmermann_invalid[actual1-predicted1-kwargs1-at least 2 values] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_cusum_ols PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_compare_nested[compare_j] PASSED [ 43%] statsmodels/stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_rainbow PASSED [ 43%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepDefault::test_basic PASSED [ 43%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepDefault::test_other PASSED [ 43%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepDefault::test_summary PASSED [ 43%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostep::test_basic PASSED [ 43%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostep::test_other PASSED [ 43%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostep::test_summary PASSED [ 43%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultOnestep::test_other PASSED [ 43%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultOnestep::test_basic PASSED [ 44%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultOnestep::test_summary PASSED [ 44%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepCenter::test_other PASSED [ 44%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepCenter::test_summary PASSED [ 44%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepCenter::test_more PASSED [ 44%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepCenter::test_basic PASSED [ 44%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddTwostep::test_summary PASSED [ 44%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddTwostep::test_other PASSED [ 44%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddTwostep::test_basic PASSED [ 44%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddOnestep::test_summary PASSED [ 44%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddOnestep::test_basic PASSED [ 44%] statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddOnestep::test_other PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-0-False-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend_smoke[range-list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_smoke[range-list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier_smoke[range-list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend_smoke[range-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_smoke[range-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier_smoke[range-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend_smoke[int64-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_smoke[int64-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier_smoke[int64-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend_smoke[int64-list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_smoke[int64-list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier_smoke[int64-list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_smoke[int64-None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier_smoke[int64-None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend_smoke[int64-None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_smoke[range-None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier_smoke[range-None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend_smoke[range-None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period1] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_smoke[datetime-None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier_smoke[datetime-None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend_smoke[datetime-None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier_smoke[datetime-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_smoke[datetime-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend_smoke[datetime-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier_smoke[datetime-list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend_smoke[datetime-list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_smoke[datetime-list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality[datetime] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend[datetime] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_invalid_formcast_index[datetime] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier[datetime] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period0] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period2] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period3] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_time_trend_smoke[None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period6] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_smoke[fib-None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier_smoke[fib-None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend_smoke[fib-None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_smoke[fib-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend_smoke[fib-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier_smoke[fib-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend_smoke[fib-list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier_smoke[fib-list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_smoke[fib-list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality[fib] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend[fib] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_invalid_formcast_index[fib] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier[fib] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period7] FAILED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period12] FAILED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_fourier_smoke[None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period5] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period10] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period11] FAILED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period4] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier_smoke[period-None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_smoke[period-None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend_smoke[period-None] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_smoke[period-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier_smoke[period-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend_smoke[period-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend_smoke[period-list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_smoke[period-list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier_smoke[period-list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend[period] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_invalid_formcast_index[period] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier[period] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality[period] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period9] FAILED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period8] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend[int64] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality[int64] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_invalid_formcast_index[int64] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier[int64] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period8] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period9] FAILED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period10] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period7] FAILED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period6] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period11] FAILED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period4] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period12] FAILED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period5] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_fourier_smoke[False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_time_trend_smoke[False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period0] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period1] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period3] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period2] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality[range] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_time_trend[range] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_invalid_formcast_index[range] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_fourier[range] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period9] FAILED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period8] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period12] FAILED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period11] FAILED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period10] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period5] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period4] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_time_trend_smoke[list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period6] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_fourier_smoke[list] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period7] FAILED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period2] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period3] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period1] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period0] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-0-True-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-1-True-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_out_of_sample_without_in_sample[True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_invalid_freq_period PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_drop_two_consants PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-1-False-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_drop PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_index_and_terms_properties PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_check_index_type PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-0-False-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-0-False-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_forbidden_index PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-1-False-0-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-0-False-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-0-True-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_range_index_basic PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-1-True-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-0-False-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonality_time_index PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-1-False-0-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-1-False-0-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process_errors PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-1-True-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-1-False-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-0-True-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_index_like PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-1-True-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_fourier PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-1-True-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonal_period_w PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-0-False-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-0-True-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-0-True-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_additional_terms PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-1-True-0-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_range_error PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-1-False-0-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-1-True-0-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-0-False-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-0-True-0-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-0-True-0-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-1-False-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-1-True-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-0-True-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-0-False-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-1-False-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-1-False-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-0-False-0-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_determintic_term_equiv[index2] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_seasonal_from_index_err PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_time_trend_base PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-0-True-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-1-True-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-1-False-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_determintic_term_equiv[index3] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-0-False-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonal_period_a FAILED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-0-False-0-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_out_of_sample_without_in_sample[False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_determintic_term_equiv[index1] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-1-False-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_determintic_term_equiv[index0] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-1-False-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-0-True-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-1-True-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-1-False-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonal_period_q FAILED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-1-False-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-1-True-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-0-True-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-1-True-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-1-False-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-1-True-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_range_casting PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-0-True-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-0-False-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-0-False-0-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonal_period_d PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-0-True-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_unknown_freq PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_calendar_time_trend PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-0-False-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_non_unit_range PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-1-True-1-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-1-False-1-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-0-False-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-0-True-0-False] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-None-1-True-0-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-1-True-0-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[False-10-0-True-0-True] PASSED [ 44%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-10-0-False-0-True] PASSED [ 45%] statsmodels/tsa/tests/test_deterministic.py::test_deterministic_process[True-None-0-True-0-True] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula3d::test_rng_types[0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula3d::test_rvs PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula3d::test_rng_types[rng2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula3d::test_rng_types[rng1] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula::test_rng_types[rng3] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula::test_pdf PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula::test_cdf PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula::test_rvs PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula::test_rng_types[rng2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula::test_rng_types[None] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula::test_seed[random_state] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula::test_rng_types[0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula::test_seed[qmc] XFAIL [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula::test_validate_params PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula::test_seed[generator] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula::test_seed[0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula::test_seed_default_rng PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula3d::test_rng_types[0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula3d::test_rng_types[rng2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula3d::test_rng_types[rng1] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula3d::test_rvs PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestIndependenceCopula::test_rvs PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestIndependenceCopula::test_cdf PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestIndependenceCopula::test_pdf PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestIndependenceCopula::test_validate_params PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula::test_seed[random_state] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula::test_rvs PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula::test_cdf PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula::test_pdf PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula::test_seed[generator] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula::test_validate_params PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula::test_seed[0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula::test_seed[qmc] XFAIL [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula::test_rng_types[rng2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula::test_rng_types[rng3] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula::test_rng_types[0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula::test_rng_types[None] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGaussianCopula::test_seed_default_rng PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula::test_validate_params PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula::test_seed[qmc] XFAIL [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula::test_seed[0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula::test_seed[generator] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula::test_rvs PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula::test_cdf SKIPPED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula::test_pdf PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula::test_rng_types[None] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula::test_rng_types[0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula::test_seed[random_state] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula::test_rng_types[rng3] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula::test_rng_types[rng2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestStudentTCopula::test_seed_default_rng PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula::test_rng_types[0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula::test_validate_params PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula::test_rvs PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula::test_cdf PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula::test_pdf PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula::test_seed_default_rng PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula::test_seed[0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula::test_seed[generator] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula::test_rng_types[None] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula::test_rng_types[rng3] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula::test_seed[qmc] XFAIL [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula::test_seed[random_state] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula::test_rng_types[rng2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula_3d::test_rng_types[rng1] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula_3d::test_rng_types[0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula_3d::test_rvs PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestGumbelCopula_3d::test_rng_types[rng2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula_3d::test_rng_types[rng2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula_3d::test_rng_types[rng1] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula_3d::test_rvs PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestClaytonCopula_3d::test_rng_types[0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas[case2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula[case6] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas_distr[case0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula[case7] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas_distr[case1] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas[case3] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula[case5] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas_distr[case10] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas_distr[case3] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas[case1] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas[case0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula[case4] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas_distr[case2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas_distr[case7] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula[case1] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas_raise[6-case1] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas[case5] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas_raise[6-case0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas[case4] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas_distr[case6] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula[case0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula_distr[case8] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas[case6] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas_distr[case4] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula[case2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas_distr[case5] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula[case3] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula_distr[case9] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas[case7] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula_distr[case3] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_gev_genextreme[case1] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula[case12] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula[case9] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_gev_genextreme[case0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula[case8] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula_distr[case2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_gev_genextreme[case2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula[case11] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_dep[case4] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula_distr[case0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula_distr[case1] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_gev_genextreme[case3] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula[case10] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas_raise[5-case1] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas_distr[case8] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula_distr[case4] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_dep[case0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula_distr[case5] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_dep[case1] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas_distr[case9] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas_raise[5-case0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula_distr[case7] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas[case9] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas[case10] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_dep[case3] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_copula_distr[case6] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_copulas[case8] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_ev_dep[case2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_rvs_kernel_reproducible_with_rng PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_plot_scatter_given_sample PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_rvs_kernel_small_bandwidth_stays_near_source PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_student_t_copula_spearmans_rho_formula[0.9] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_tau_simulated[student_t] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_tau_simulated[gumbel] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_plot_scatter_generated_sample PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_gaussian_copula_dependence_tail PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_student_t_copula_dependence_tail_formula[0.0-6] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_tau_simulated[frank] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_student_t_copula_dependence_tail_formula[0.5-4] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_tau_simulated[gaussian] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_plot_scatter_raises_for_higher_dim PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_student_t_copula_spearmans_rho_formula[0.4] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_student_t_copula_dependence_tail_formula[-0.3-8] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_plot_pdf_grid_matches_pdf PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_student_t_copula_dependence_tail_limits PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_student_t_copula_spearmans_rho_simulated PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_student_t_copula_spearmans_rho_formula[-0.7] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_student_t_copula_dependence_tail_formula[0.8-2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_student_t_copula_spearmans_rho_formula[-0.2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_tau_simulated[clayton] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_student_t_copula_spearmans_rho_formula[0.0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::test_rvs_kernel_preserves_dependence PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula_3d::test_rng_types[rng2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula_3d::test_rng_types[rng1] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula_3d::test_rng_types[0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula_3d::test_rvs PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrank::test_tau PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrank::test_basic PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula::test_seed[generator] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula::test_seed[0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula::test_validate_params PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula::test_rng_types[0] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula::test_cdf PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula::test_rvs PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula::test_pdf PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula::test_rng_types[None] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula::test_rng_types[rng2] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula::test_rng_types[rng3] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula::test_seed[random_state] PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula::test_seed_default_rng PASSED [ 45%] statsmodels/distributions/copula/tests/test_copula.py::TestFrankCopula::test_seed[qmc] XFAIL [ 45%] statsmodels/discrete/tests/test_conditional.py::test_skip_hessian PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_summary_after_remove_data[ConditionalLogit] PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_conditional_mnlogit_fit_rng_types[randomstate] PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_formula PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_logit_formula PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_conditional_mnlogit_fit_rng_types[int] PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_conditional_mnlogit_fit_warn PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_logit_1d PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_summary_after_remove_data[ConditionalPoisson] PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_summary_after_remove_data[ConditionalMNLogit] PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_logit_2d PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_lasso_logistic PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_lasso_poisson PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_fit_regularized_invalid_method PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_conditional_mnlogit_fit_rng_reproducible PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_poisson_2d PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_conditional_mnlogit_2d PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_conditional_mnlogit_grad PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_conditional_mnlogit_fit_rng_types[generator] PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_conditional_mnlogit_3d PASSED [ 45%] statsmodels/discrete/tests/test_conditional.py::test_poisson_1d PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJoh12::test_basic PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJoh12::test_evals PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJoh12::test_evec PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJoh12::test_table_trace PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJoh12::test_table_maxeval PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJoh12::test_normalization PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJohMin18::test_normalization PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJohMin18::test_table_maxeval PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJohMin18::test_basic PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJohMin18::test_table_trace PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::test_coint_johansen_0lag PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::test_johansen_result_aliases_and_rkt_meth PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJoh09::test_table_trace PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJoh09::test_basic PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJoh09::test_normalization PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJoh09::test_table_maxeval PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJoh25::test_table_trace PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJoh25::test_basic PASSED [ 45%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJoh25::test_table_maxeval PASSED [ 46%] statsmodels/tsa/vector_ar/tests/test_coint.py::TestCointJoh25::test_normalization PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingPartial::test_loglike PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingPartial::test_simulate_1 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingPartial::test_simulation_smoothing_1 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingPartial::test_simulate_0 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingPartial::test_simulation_smoothing_0 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingPartial::test_simulation_smoothing_2 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingPartial::test_simulate_2 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnown::test_simulate_0 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnown::test_simulation_smoothing_0 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnown::test_loglike PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnown::test_simulate_1 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnown::test_simulation_smoothing_1 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnown::test_simulation_smoothing_2 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnown::test_simulate_2 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingMixed::test_simulate_2 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingMixed::test_simulation_smoothing_1 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingMixed::test_simulation_smoothing_0 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingMixed::test_simulation_smoothing_2 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingMixed::test_simulate_1 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingMixed::test_loglike PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingMixed::test_simulate_0 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingAll::test_simulation_smoothing_0 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingAll::test_simulate_1 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingAll::test_loglike PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingAll::test_simulate_0 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingAll::test_simulation_smoothing_1 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingAll::test_simulate_2 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingAll::test_simulation_smoothing_2 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::test_nan PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::test_misc PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::test_simulation_smooth_results_output_flag_properties PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::test_simulation_smoother_invalid_method_raises PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::test_simulation_smoothing_state_intercept_diffuse PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::test_simulation_smoothing_state_intercept PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::test_simulation_smoothing_obs_intercept PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestDFM::test_simulate_0 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestDFM::test_loglike PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestDFM::test_simulation_smoothing_1 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestDFM::test_simulation_smoothing_0 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestDFM::test_simulate_1 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestDFM::test_simulation_smoothing_2 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestDFM::test_simulate_2 PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVAR::test_simulation_smoothing PASSED [ 46%] statsmodels/tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVAR::test_loglike PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_medcouple_nonzero PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_medcouple_r_reference_ties PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_durbin_watson_3d PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_medcouple_symmetric PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_durbin_watson_2d PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_medcouple_ties PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_robust_kurtosis_1d_2d PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_medcouple_large_random PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_medcouple_even_hcount_regression PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_robust_skewness_1d_2d PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_robust_kurtosis_excess_false PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_durbin_watson PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_medcouple_short_input PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_robust_kurtosis_dg PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_robust_kurtosis_ab PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_medcouple_1d PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_medcouple_axis_consistency PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_medcouple_symmetry PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_medcouple_r_reference_majority_tied PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_medcouple_no_axis PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_robust_kurtosis PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_robust_skewness_4 PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_robust_skewness_3d PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_medcouple_int PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_medcouple_nan_propagation PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_medcouple_consistency_fast_vs_legacy PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_robust_kurtosis_3d PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_robust_skewness_1d PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::TestStattools::test_robust_skewness_symmetric PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::test_omni_normtest PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::test_adnorm PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::test_jarque_bera PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::test_omni_normtest_axis PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::test_shapiro PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::test_durbin_watson_pandas PASSED [ 46%] statsmodels/stats/tests/test_statstools.py::test_durbin_watson PASSED [ 46%] statsmodels/stats/tests/test_groups_sw.py::TestBalanced::test_raises PASSED [ 46%] statsmodels/stats/tests/test_groups_sw.py::TestBalanced::test_values PASSED [ 46%] statsmodels/stats/tests/test_groups_sw.py::TestUnBalanced::test_raises PASSED [ 46%] statsmodels/stats/tests/test_groups_sw.py::TestUnBalanced::test_values PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_runstest_2sample PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_mcnemar_exact PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_jonckheere_terpstra_invalid[samples4-larger-one-dimensional] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_mcnemar_vectorized PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_jonckheere_terpstra_invalid[samples0-larger-at least two ordered samples] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_symmetry_bowker PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_jonckheere_terpstra_invalid[samples1-larger-zero length] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_jonckheere_terpstra_smaller_and_two_sided PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_jonckheere_terpstra_invalid[samples2-invalid-alternative] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_brunnermunzel_one_sided PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_samplesize_rank_compare_onetail_invalid[synthetic_sample10-reference_sample10-0.05-0.8-1.0-smaller-ValueError-Estimated relative effect is larger than 0.5] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_cochransq PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_samplesize_rank_compare_onetail_invalid[synthetic_sample0-reference_sample0-0.0-0.8-1.0-two-sided-ValueError-Alpha must be between 0 and 1] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_rank_compare_2indep1 PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_jonckheere_terpstra_many_unequal_groups PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_jonckheere_terpstra_stats_api_export PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_samplesize_rank_compare_onetail_invalid[synthetic_sample9-reference_sample9-0.05-0.8-0.5-invalid-alternative-ValueError-alternative] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_jonckheere_terpstra_known_extreme_statistic PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_samplesize_rank_compare_onetail_invalid[synthetic_sample12-reference_sample12-0.05-0.8-1.0-two-sided-ValueError-Estimated relative effect is effectively 0.5] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_rank_compare_ord PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_samplesize_rank_compare_onetail_invalid[synthetic_sample1-reference_sample1-1.0-0.8-1.0-two-sided-ValueError-Alpha must be between 0 and 1] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_samplesize_rank_compare_onetail_invalid[synthetic_sample8-reference_sample8-0.05-0.8-0.5-False-TypeError-alternative must be a string] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_compute_rank_placements[test_cases1] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_samplesize_rank_compare_onetail_invalid[synthetic_sample6-reference_sample6-0.05-0.8-0.5-one-sided-ValueError-All elements of `synthetic_sample` and `reference_sample` must be finite; check for missing values.] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_cochransq3 PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_jonckheere_terpstra_invalid[samples3-larger-variance is zero] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_jonckheere_terpstra_minimal_nobs PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_compute_rank_placements[test_cases0] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_runstest PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_samplesize_rank_compare_onetail_invalid[synthetic_sample2-reference_sample2-0.05-0.0-1.0-one-sided-ValueError-Power must be between 0 and 1] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_samplesize_rank_compare_onetail_invalid[synthetic_sample5-reference_sample5-0.05-0.8--1.0-one-sided-ValueError-Ratio of reference group to treatment group must be strictly positive.] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_rank_compare_vectorized PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_compute_rank_placements[test_cases2] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_jonckheere_terpstra_exceptions PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_samplesize_rank_compare_onetail_invalid[synthetic_sample4-reference_sample4-0.05-0.8-0.0-one-sided-ValueError-Ratio of reference group to treatment group must be strictly positive.] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_mcnemar_chisquare PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_samplesize_rank_compare_onetail PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_samplesize_rank_compare_onetail_invalid[synthetic_sample7-reference_sample7-0.05-0.8-0.5-one-sided-ValueError-Both `synthetic_sample` and `reference_sample` must have at least one element] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_samplesize_rank_compare_onetail_invalid[synthetic_sample11-reference_sample11-0.05-0.8-1.0-larger-ValueError-Estimated relative effect is smaller than 0.5] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_brunnermunzel_two_sided PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_samplesize_rank_compare_onetail_invalid[synthetic_sample3-reference_sample3-0.05-1.0-1.0-one-sided-ValueError-Power must be between 0 and 1] PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_jonckheere_terpstra_result_type PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_cochransq2 PASSED [ 46%] statsmodels/stats/tests/test_nonparametric.py::test_jonckheere_terpstra_larger_matches_kendalltau PASSED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_run[series] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_select_order[monthly-False] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_run[monthly] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_no_save[monthly_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_invalid_rawspec[monthly_start_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_plot_no_pandas[monthly_start_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_log_diagnostics[dataframe] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_log_diagnostics_false[monthly_start_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_log_diagnostics[series] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_plot_no_pandas[monthly_start] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_log_diagnostics_false[monthly_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_select_order[monthly_co2-True] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_plot[monthly_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_select_order[monthly_start_co2-False] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_no_save[monthly] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_select_order[series-True] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_select_order[monthly_start-False] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_plot_no_pandas[monthly_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_select_order[dataframe-True] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_no_x11[monthly] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_log_diagnostics[monthly_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_select_order[monthly_start-True] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_select_order[monthly-True] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_log_diagnostics[monthly] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_run[dataframe] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_plot[dataframe] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_no_save[dataframe] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_no_x11[series] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_arg SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_plot[monthly_start_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_log_diagnostics[monthly_start] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_plot[monthly_start] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_invalid_rawspec[dataframe] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_invalid_rawspec[series] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_plot[series] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_select_order[monthly_co2-False] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_run[monthly_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_invalid_rawspec[monthly_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_log_diagnostics_false[monthly_start] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_select_order[monthly_start_co2-True] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_select_order[series-False] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_plot_no_pandas[monthly] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_invalid_rawspec[monthly] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_no_x11[dataframe] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_no_save[series] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_no_save[monthly_start_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_plot_no_pandas[series] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_plot[monthly] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_no_x11[monthly_start] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_invalid_rawspec[monthly_start] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_log_diagnostics[monthly_start_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_select_order[dataframe-False] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_no_save[monthly_start] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_run[monthly_start_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_run[monthly_start] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_plot_no_pandas[dataframe] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_no_x11[monthly_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_log_diagnostics_false[dataframe] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_log_diagnostics_false[series] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_x13_arima_rawspec_no_x11[monthly_start_co2] SKIPPED [ 46%] statsmodels/tsa/tests/test_x13.py::test_log_diagnostics_false[monthly] SKIPPED [ 46%] statsmodels/gam/tests/test_smooth_basis.py::test_get_knots_bsplines_spacing_equal_few_inner_knots[5-3-1] PASSED [ 46%] statsmodels/gam/tests/test_smooth_basis.py::test_get_knots_bsplines_spacing_equal_unchanged_for_multiple_inner_knots PASSED [ 46%] statsmodels/gam/tests/test_smooth_basis.py::test_bsplines[x1-6-3] PASSED [ 46%] statsmodels/gam/tests/test_smooth_basis.py::test_multivariate_polynomial_basis PASSED [ 46%] statsmodels/gam/tests/test_smooth_basis.py::test_get_knots_bsplines_spacing_equal_few_inner_knots[4-2-1] PASSED [ 46%] statsmodels/gam/tests/test_smooth_basis.py::test_get_knots_bsplines_spacing_equal_few_inner_knots[3-2-0] PASSED [ 46%] statsmodels/gam/tests/test_smooth_basis.py::test_cubic_splines_transform_not_shadowed PASSED [ 46%] statsmodels/gam/tests/test_smooth_basis.py::test_univariate_polynomial_smoother PASSED [ 46%] statsmodels/gam/tests/test_smooth_basis.py::test_bsplines[x0-df0-degree0] PASSED [ 46%] statsmodels/gam/tests/test_smooth_basis.py::test_get_knots_bsplines_spacing_equal_few_inner_knots[4-3-0] PASSED [ 46%] statsmodels/gam/tests/test_smooth_basis.py::test_get_knots_bsplines_spacing PASSED [ 46%] statsmodels/treatment/tests/test_teffects.py::TestTEffects::test_effects[case4] PASSED [ 46%] statsmodels/treatment/tests/test_teffects.py::TestTEffects::test_effects[case3] PASSED [ 46%] statsmodels/treatment/tests/test_teffects.py::TestTEffects::test_effects[case2] PASSED [ 46%] statsmodels/treatment/tests/test_teffects.py::TestTEffects::test_effects[case0] PASSED [ 46%] statsmodels/treatment/tests/test_teffects.py::TestTEffects::test_effects[case1] PASSED [ 46%] statsmodels/treatment/tests/test_teffects.py::TestTEffects::test_aux PASSED [ 46%] statsmodels/treatment/tests/test_teffects.py::TestTEffects::test_method_label[case4] PASSED [ 46%] statsmodels/treatment/tests/test_teffects.py::TestTEffects::test_method_label[case0] PASSED [ 46%] statsmodels/treatment/tests/test_teffects.py::TestTEffects::test_method_label[case1] PASSED [ 46%] statsmodels/treatment/tests/test_teffects.py::TestTEffects::test_method_label[case3] PASSED [ 46%] statsmodels/treatment/tests/test_teffects.py::TestTEffects::test_method_label[case2] PASSED [ 46%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleNegbinSimulated::test_predict PASSED [ 46%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleNegbinSimulated::test_basic PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleNegbinSimulated::test_hessian_numerical PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleNegbinSimulated::test_score_numerical PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleNegbinSimulated::test_score_consistency PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleL1::test_nnz_params <- discrete/tests/test_discrete.py PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleL1::test_bse <- discrete/tests/test_discrete.py PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleL1::test_aic <- discrete/tests/test_discrete.py PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleL1::test_bic <- discrete/tests/test_discrete.py PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleL1::test_conf_int <- discrete/tests/test_discrete.py PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleL1::test_bse_agrees_with_trimmed PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleL1::test_params <- discrete/tests/test_discrete.py PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedLFPoisson_predict::test_predict_prob PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedLFPoisson_predict::test_mean PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedLFPoisson_predict::test_var PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestZeroTruncatedLFPoissonModel::test_bse PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestZeroTruncatedLFPoissonModel::test_llf PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestZeroTruncatedLFPoissonModel::test_aic PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestZeroTruncatedLFPoissonModel::test_bic PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestZeroTruncatedLFPoissonModel::test_params PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestZeroTruncatedLFPoissonModel::test_fit_regularized PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestZeroTruncatedLFPoissonModel::test_conf_int PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedLFPoissonModel::test_bse PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedLFPoissonModel::test_llf PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedLFPoissonModel::test_bic PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedLFPoissonModel::test_aic PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedLFPoissonModel::test_conf_int PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedLFPoissonModel::test_params PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedLFPoissonModel::test_fit_regularized XFAIL [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedNegBinSt::test_predict PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedNegBinSt::test_basic PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedNegBinSt::test_offset PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdlePoissonR::test_predict PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdlePoissonR::test_basic PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedLFPoissonSt::test_predict PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedLFPoissonSt::test_basic PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedLFPoissonSt::test_offset PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedNBP_predict::test_var PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedNBP_predict::test_predict_prob PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedNBP_predict::test_mean PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestRegularizedHurdleSimulated::test_predict PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestRegularizedHurdleSimulated::test_score_numerical PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestRegularizedHurdleSimulated::test_hessian_numerical PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestRegularizedHurdleSimulated::test_basic PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestRegularizedHurdleSimulated::test_bse_agrees_with_trimmed PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestRegularizedHurdleSimulated::test_score_consistency PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedLFPoisson1St::test_basic PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedLFPoisson1St::test_predict PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::test_truncated_negative_binomial_dispersion_factor PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::test_summary_after_remove_data[HurdleCountModel] PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::test_summary_after_remove_data[TruncatedLFPoisson] PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::test_summary_after_remove_data[TruncatedLFNegativeBinomialP] PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::test_truncated_poisson_dispersion_factor PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::test_fit_regularized_converged_reports_joint_fit_too PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::test_fit_start_params_wrong_size_raises_clear_error PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[poisson-poisson] PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-poisson] PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[poisson-negbin] PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleL1Compatibility::test_t_test PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleL1Compatibility::test_df <- discrete/tests/test_discrete.py PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleL1Compatibility::test_f_test PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleL1Compatibility::test_cov_params PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleL1Compatibility::test_bad_r_matrix <- discrete/tests/test_discrete.py PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestHurdleL1Compatibility::test_params PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedNegBin1St::test_basic PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestTruncatedNegBin1St::test_predict PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestZeroTruncatedNBPModel::test_fit_regularized PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestZeroTruncatedNBPModel::test_params PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestZeroTruncatedNBPModel::test_aic PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestZeroTruncatedNBPModel::test_bic PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestZeroTruncatedNBPModel::test_llf PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestZeroTruncatedNBPModel::test_bse PASSED [ 47%] statsmodels/discrete/tests/test_truncated_model.py::TestZeroTruncatedNBPModel::test_conf_int PASSED [ 47%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_em_nonstationary PASSED [ 47%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_two_blocks_factor_orders_6 SKIPPED [ 47%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_k_factor1 SKIPPED [ 47%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_k_factor1_factor_order_6 PASSED [ 47%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_k_factor2_factor_order_6 SKIPPED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_null_odds PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_from_data PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_oddsratio_pooled PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_pandas PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_logodds_pooled_confint PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_equal_odds PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_oddsratio_pooled_confint PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_logodds_pooled PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified3::test_pandas PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified3::test_oddsratio_pooled_confint PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified3::test_equal_odds PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified3::test_null_odds PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified3::test_logodds_pooled_confint PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified3::test_from_data PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified3::test_oddsratio_pooled PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::TestStratified3::test_logodds_pooled PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::Test2x2_1::test_riskratio_confint PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::Test2x2_1::test_log_oddsratio PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::Test2x2_1::test_summary PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::Test2x2_1::test_log_riskratio_se PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::Test2x2_1::test_from_data PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::Test2x2_1::test_oddsratio_pvalue PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::Test2x2_1::test_oddsratio PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::Test2x2_1::test_riskratio_pvalue PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::Test2x2_1::test_oddsratio_confint PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::Test2x2_1::test_log_riskratio PASSED [ 47%] statsmodels/stats/tests/test_contingency_tables.py::Test2x2_1::test_log_oddsratio_se PASSED [ 47%] 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PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma_exogenous::test_init_keys_replicate PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma::test_init_keys_replicate PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma::test_plot_diagnostics PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma::test_transform_untransform PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma::test_start_params PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma::test_results PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma::test_loglike PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma::test_predict PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineStateDifferencing::test_bse_approx PASSED [ 48%] 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statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_predict PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_loglike PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_results PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_plot_diagnostics PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_start_params PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_transform_untransform PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_init_keys_replicate PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma::test_plot_diagnostics PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma::test_start_params PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma::test_transform_untransform PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma::test_results PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma::test_loglike PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma::test_predict PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma::test_init_keys_replicate PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_c::test_plot_diagnostics PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_c::test_results PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_c::test_loglike PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_c::test_predict PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_c::test_transform_untransform PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_c::test_start_params PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_c::test_init_keys_replicate PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_trend_polynomial::test_init_keys_replicate PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_trend_polynomial::test_plot_diagnostics PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_trend_polynomial::test_start_params PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_trend_polynomial::test_transform_untransform PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_trend_polynomial::test_results PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_trend_polynomial::test_loglike PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_trend_polynomial::test_predict PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_loglike PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_aic PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_bic PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_hqic PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_bse PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_mle PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_t_test PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_seasonal_diff::test_loglike PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_seasonal_diff::test_predict PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_seasonal_diff::test_results PASSED [ 48%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_seasonal_diff::test_init_keys_replicate PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_seasonal_diff::test_start_params PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_seasonal_diff::test_plot_diagnostics PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_seasonal_diff::test_transform_untransform PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_polynomial::test_transform_untransform PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_polynomial::test_start_params PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_polynomial::test_plot_diagnostics PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_polynomial::test_init_keys_replicate PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_polynomial::test_loglike PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_polynomial::test_predict PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_polynomial::test_results PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_ct::test_predict PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_ct::test_loglike PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_ct::test_results PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_ct::test_plot_diagnostics PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_ct::test_start_params PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_ct::test_init_keys_replicate PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_ct::test_transform_untransform PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma::test_transform_untransform PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma::test_init_keys_replicate PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma::test_results PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma::test_loglike PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma::test_predict PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma::test_plot_diagnostics PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma::test_start_params PASSED [ 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statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_trend_c::test_loglike PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_trend_c::test_predict PASSED [ 49%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_trend_c::test_results PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::TestSeasonalARMADiffuse::test_results PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::TestSeasonalARMADiffuse::test_predict PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::TestSeasonalARMADiffuse::test_loglike PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::TestSeasonalARMADiffuse::test_transform_untransform PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::TestSeasonalARMADiffuse::test_init_keys_replicate PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::TestSeasonalARMADiffuse::test_start_params PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::TestSeasonalARMADiffuse::test_plot_diagnostics PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous_not_hamilton::test_results PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous_not_hamilton::test_loglike PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous_not_hamilton::test_predict PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous_not_hamilton::test_plot_diagnostics PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous_not_hamilton::test_transform_untransform PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous_not_hamilton::test_init_keys_replicate PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous_not_hamilton::test_start_params PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_plot_diagnostics PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_start_params PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_init_keys_replicate PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_transform_untransform PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_results PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_predict PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_loglike PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diff::test_transform_untransform PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diff::test_start_params PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diff::test_plot_diagnostics PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diff::test_init_keys_replicate PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diff::test_predict PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diff::test_loglike PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diff::test_results PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_c::test_plot_diagnostics PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_c::test_start_params PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_c::test_transform_untransform PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_c::test_results PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_c::test_loglike PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_c::test_predict PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_c::test_init_keys_replicate PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_seasonal_diff::test_predict PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_seasonal_diff::test_loglike PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_seasonal_diff::test_results PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_seasonal_diff::test_plot_diagnostics PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_seasonal_diff::test_start_params PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_seasonal_diff::test_init_keys_replicate PASSED [ 50%] statsmodels/tsa/statespace/tests/test_sarimax.py::Test_arma_seasonal_diff::test_transform_untransform PASSED [ 50%] statsmodels/stats/tests/test_contrast.py::TestContrast::test_contrast2 PASSED [ 50%] statsmodels/stats/tests/test_contrast.py::TestContrast::test_contrast3 PASSED [ 50%] statsmodels/stats/tests/test_contrast.py::TestContrast::test_contrast1 PASSED [ 50%] statsmodels/stats/tests/test_contrast.py::TestContrast::test_estimable PASSED [ 50%] statsmodels/stats/tests/test_contrast.py::test_wald_test_results_summary_frame_str_repr PASSED [ 50%] statsmodels/stats/tests/test_contrast.py::test_contrast_results_str_repr PASSED [ 50%] statsmodels/stats/tests/test_contrast.py::test_constraints PASSED [ 50%] statsmodels/stats/tests/test_contrast.py::test_wald_test_results_direct_construction PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_leave_one_label_out_does_not_mutate_input PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_leave_one_label_out PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_kstepahead_boolean_mode_matches_slice_mode PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_kfold_partitions_all_indices_without_overlap PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_leave_one_out_repr PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_split PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_kfold_k_equal_one_is_degenerate PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_kfold_fold_sizes_use_ceil_not_trunc PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_leave_p_out_repr PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_leave_one_label_out_repr PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_kfold_invalid_k_raises_assertion_error_not_value_error PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_kfold_repr PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_kstepahead_slice_mode_kall_false PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_split_accepts_list_input PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_kstepahead_slice_mode_default_kall PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_leave_p_out PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_kstepahead_repr PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_leave_one_out PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_kstepahead_default_start_is_quarter_of_n PASSED [ 50%] statsmodels/sandbox/tools/tests/test_cross_val.py::test_split_single_array PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-ssr] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-ess] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-ess] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-ess] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-rsquared] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-ssr] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-ess] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-ess] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-ssr] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-ssr] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-ess] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-rsquared] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-ess] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-ssr] PASSED [ 50%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-ess] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-ess] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-rsquared] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-ssr] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-rsquared] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-ess] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-ssr] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-ess] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-ssr] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-ess] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-ess] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-ssr] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-ess] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-ssr] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-ess] PASSED [ 51%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-rsquared] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-ssr] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-ess] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-rsquared] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-ssr] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-ess] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-ess] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-ssr] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-ess] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-ssr] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-rsquared] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-ssr] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-ess] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-ess] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-ssr] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-ess] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 52%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-ssr] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-ess] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-ess] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-rsquared] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-ess] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-ssr] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-rsquared] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-ess] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-ssr] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-ssr] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-ess] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 53%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-ssr] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-ess] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-ess] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-ssr] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-rsquared] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-ess] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-ssr] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_forecast_start_end_equiv[False] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-ssr] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-ess] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-rsquared] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-ess] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-ess] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 54%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-rsquared] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-ssr] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-rsquared] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-ess] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-ssr] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-ssr] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-ess] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-ess] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-ssr] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-ess] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-ess] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-ess] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-ess] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-rsquared] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-ssr] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-ssr] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-ess] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-rsquared] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-rsquared] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-ssr] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-ess] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 55%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-ssr] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-rsquared] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-ess] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-ssr] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-ess] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-ssr] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-ess] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-ess] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-rsquared] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-ssr] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-ess] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-ess] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_summary_after_remove_data[2-True] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-ssr] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-ess] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-ess] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-ssr] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 56%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_removal PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-ess] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-ssr] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-ssr] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-ess] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-ess] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-ssr] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-ssr] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-ess] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-ssr] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-ess] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-rsquared] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 57%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-ssr] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-rsquared] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-ess] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-ssr] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-ess] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-rsquared] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-ess] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-ess] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-ssr] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-ssr] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-ess] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-ess] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-ess] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-ssr] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 58%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-ssr] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-rsquared] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-ess] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-rsquared] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-ess] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-ssr] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-ess] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-ess] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-rsquared] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-ssr] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-ess] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 59%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-ssr] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-ess] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-ess] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag5] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-ess] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-ssr] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-rsquared] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-ess] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-ess] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-ssr] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-ess] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 60%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-rsquared] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-ssr] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-ess] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-ess] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-ssr] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-ess] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-ess] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-ssr] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-rsquared] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-rsquared] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-ssr] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-ess] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-ess] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 61%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-ess] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-ssr] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-ess] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-ess] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-ssr] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-ess] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-ess] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-ess] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 62%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag4] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-ess] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-ess] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-ess] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-ssr] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-uncentered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-rsquared] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-ess] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-centered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-ess] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-centered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-uncentered_tss] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-ess] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 63%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-rsquared] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-ssr] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back: 12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-rsquared] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-ess] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-ssr] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[False-0-False-ct] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-ess] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-ssr] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-rsquared] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_predictions_oos PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag6] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-uncentered_tss] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-centered_tss] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-ess] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-rsquared] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-ssr] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_forecast_period_index PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_ar_select_order_invalid_ic_raises PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 64%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_resids PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_predict_errors PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-uncentered_tss] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-centered_tss] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-ssr] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-rsquared] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-ess] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-1-False-ct] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 65%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_deterministic PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back: 12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_plot_err PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag7] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_predict_ar_constant PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back: 12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag2] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_series PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[False-3-True-n] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 66%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-0-True-ct] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_parameterless_autoreg PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_ar_select_order_smoke PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_score PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag3] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-3-True-n] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 67%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back: 12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_predict_ar_no_constant PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_predict_seasonal PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[False-0-False-n] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-0-True-n] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_invalid_dynamic PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[False-0-True-ct] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-3-False-ct] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag1] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[False-1-True-n] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 68%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_apply_exception PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag0] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_exog_prediction PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-1-True-n] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_diagnostic_summary_short PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[False-0-True-n] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back: None] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-0-False-n] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_equiv_dynamic PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_new_names PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[False-3-False-ct] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_roots PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[False-3-True-ct] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_spec_errors PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[False-1-True-ct] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 69%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back: None] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag15] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back: None] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_constant_column_trend PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_summary_after_remove_data[0-False] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_named_series PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_summary_corner PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-1-False-n] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag14] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-3-False-n] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back: None] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_against_sarimax PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_summary_after_remove_data[0-True] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-3-True-ct] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag9] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-1-True-ct] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back: None] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_start[25] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[False-1-False-n] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[False-3-False-n] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag8] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 70%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_ar_select_order_ics_are_information_criteria PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_ar_order_select PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back: 12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append_deterministic PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_summary_after_remove_data[2-False] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_start[21] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back: None] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back: 12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[False-1-False-ct] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_no_variables PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag13] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_predictions PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back: None] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back: 12] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_predict_irregular_ar PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag11] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_forecast_start_end_equiv[True] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-0-False-ct] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_ar_model_predict PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_no_obs_for_adjustment PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag10] PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_forecast_equiv PASSED [ 71%] statsmodels/tsa/tests/test_ar.py::test_predict_exog PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestDFMPartialMissing::test_posterior_mean PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestDFMPartialMissing::test_posterior_cov PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestSARIMAXMEMissing::test_posterior_cov PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestSARIMAXMEMissing::test_posterior_mean PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestUnobservedComponentsMissing::test_posterior_mean PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestUnobservedComponentsMissing::test_posterior_cov PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestDFMComplex::test_posterior_mean PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestDFMComplex::test_posterior_cov PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestSARIMAXME::test_posterior_mean PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestSARIMAXME::test_posterior_cov PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestVARME::test_posterior_cov PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestVARME::test_posterior_mean PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestVARMEAllMissing::test_posterior_cov PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestVARMEAllMissing::test_posterior_mean PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::test_dfm PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestVARMEPartialMissing::test_posterior_cov PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestVARMEPartialMissing::test_posterior_mean PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestVARMEMixedMissing::test_posterior_mean PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestVARMEMixedMissing::test_posterior_cov PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestDFMMixedMissing::test_posterior_cov PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestDFMMixedMissing::test_posterior_mean PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestUnobservedComponents::test_posterior_mean PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestUnobservedComponents::test_posterior_cov PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestDFM::test_posterior_mean PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestDFM::test_posterior_cov PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestDFMAllMissing::test_posterior_mean PASSED [ 71%] statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py::TestDFMAllMissing::test_posterior_cov PASSED [ 71%] statsmodels/tools/tests/test_linalg.py::test_stationary_solve_2d PASSED [ 71%] statsmodels/tools/tests/test_linalg.py::test_stationary_solve_1d PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGAMMPG::test_fitted PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGAMMPG::test_exog PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGAM6Bfgs::test_fitted PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGLMPenalizedPLS5::test_params PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGLMPenalizedPLS5::test_null_smoke PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGLMPenalizedPLS5::test_fitted PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGAMMPGBSPoissonFormula::test_wald PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGAMMPGBSPoissonFormula::test_null_smoke PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGAMMPGBSPoissonFormula::test_edf PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGAMMPGBSPoissonFormula::test_params PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGAMMPGBSPoissonFormula::test_predict PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGAMMPGBSPoissonFormula::test_select_alpha PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGAMMPGBSPoissonFormula::test_fitted PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGAMMPGBSPoissonFormula::test_smooth PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGAMMPGBSPoissonFormula::test_names_wrapper PASSED [ 71%] statsmodels/gam/tests/test_penalized.py::TestGAM6ExogBfgs::test_exog PASSED [ 71%] 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[ 72%] statsmodels/duration/tests/test_survfunc.py::test_survfunc_entry_3 PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_kernel_survfunc2 PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_survdiff_entry_3 PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_incidence PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_survdiff_entry_2 PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_survfunc_entry_2 PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_kernel_survfunc3 PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_survfunc1 PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_bmt PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_kernel_cumincidence2 PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_weights1 PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_plot_km PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_kernel_survfunc1 PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_survfunc2 PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_survfunc_entry_1 PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_survdiff_basic PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_survdiff_entry_1 PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_incidence2 PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_survdiff PASSED [ 72%] statsmodels/duration/tests/test_survfunc.py::test_simultaneous_cb PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::TestMICE::test_MICE1 PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::TestMICE::test_MICE2 PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::TestMICE::test_MICE PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::TestMICE::test_MICE1_regularized PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::TestMICEData::test_split_data_predict_kwds_use_missing_rows PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::TestMICEData::test_plot_missing_pattern PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::TestMICEData::test_default PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::TestMICEData::test_plot_bivariate PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::TestMICEData::test_settingwithcopywarning PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::TestMICEData::test_set_imputer PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::TestMICEData::test_fit_obs PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::TestMICEData::test_pertmeth PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::TestMICEData::test_next_sample PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::TestMICEData::test_plot_imputed_hist PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::TestMICEData::test_phreg PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::test_micedata_miss1 PASSED [ 72%] statsmodels/imputation/tests/test_mice.py::test_mice_data_iterable PASSED [ 72%] statsmodels/tools/tests/test_parallel.py::test_parallel PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests2::test_multi_pvalcorrection_rmethods[Holm-val4] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests2::test_multi_pvalcorrection PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests2::test_multi_pvalcorrection_rmethods[Bonferroni-val2] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests2::test_multi_pvalcorrection_rmethods[rawp-val8] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests2::test_multi_pvalcorrection_rmethods[SidakSS-val6] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests2::test_multi_pvalcorrection_rmethods[BY-val1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests2::test_multi_pvalcorrection_rmethods[Hochberg-val3] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests2::test_multi_pvalcorrection_rmethods[BH-val0] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests2::test_multi_pvalcorrection_rmethods[SidakSD-val5] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests2::test_multi_pvalcorrection_rmethods[TSBH_0.05-val7] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests3::test_multi_pvalcorrection_rmethods[rawp-val8] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests3::test_multi_pvalcorrection_rmethods[SidakSD-val5] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests3::test_multi_pvalcorrection_rmethods[BY-val1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests3::test_multi_pvalcorrection PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests3::test_multi_pvalcorrection_rmethods[Bonferroni-val2] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests3::test_multi_pvalcorrection_rmethods[Holm-val4] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests3::test_multi_pvalcorrection_rmethods[SidakSS-val6] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests3::test_multi_pvalcorrection_rmethods[TSBH_0.05-val7] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests3::test_multi_pvalcorrection_rmethods[BH-val0] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests3::test_multi_pvalcorrection_rmethods[Hochberg-val3] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests1::test_multi_pvalcorrection PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests1::test_multi_pvalcorrection_rmethods[Bonferroni-val2] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests1::test_multi_pvalcorrection_rmethods[BH-val0] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests1::test_multi_pvalcorrection_rmethods[Hochberg-val3] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests1::test_multi_pvalcorrection_rmethods[Holm-val4] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests1::test_multi_pvalcorrection_rmethods[SidakSD-val5] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests1::test_multi_pvalcorrection_rmethods[TSBH_0.05-val7] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests1::test_multi_pvalcorrection_rmethods[rawp-val8] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests1::test_multi_pvalcorrection_rmethods[SidakSS-val6] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::TestMultiTests1::test_multi_pvalcorrection_rmethods[BY-val1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_local_fdr_correction_against_r_fdrtool[pvals1-0.7-expected_fdr1-expected_lfdr1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_local_fdr_correction_against_r_fdrtool[pvals0-1.0-expected_fdr0-expected_lfdr0] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_local_fdr_correction_against_r_fdrtool[pvals3-1.0-expected_fdr3-expected_lfdr3] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_local_fdr_correction_against_r_fdrtool[pvals2-0.9-expected_fdr2-expected_lfdr2] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_local_fdr_correction_reference PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-fdr_i-0.05] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-b-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-hommel-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-fdr_gbs-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_floating_precision[sh] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-hs-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-fdr_gbs-0.05] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-s-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-hommel-0.01] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-fdr_i-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_issorted[fdr_bh] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-b-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-fdr_i-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-h-0.01] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-h-0.05] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-s-0.05] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-s-0.01] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-fdr_tsbky-0.05] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-hs-0.01] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-sh-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-s-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-fdr_tsbh-0.05] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-fdr_tsbky-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-fdr_tsbky-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-fdr_i-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-fdr_tsbh-0.01] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-s-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-fdr_gbs-0.01] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_fdr_bky PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-fdr_gbs-0.05] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-fdr_n-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_null_constrained[False-True-False] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-hs-0.01] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-fdr_n-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-b-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-b-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-hs-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_issorted[fdr_gbs] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-fdr_n-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-hs-0.01] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-fdr_n-0.05] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-fdr_tsbh-0.01] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-sh-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-hs-0.01] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-fdr_tsbh-0.1] PASSED [ 72%] statsmodels/stats/tests/test_multi.py::test_multipletests_empty[lfdr] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-fdr_n-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-fdr_tsbky-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-s-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-s-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-h-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-h-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-hommel-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-hs-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-hs-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_null_constrained[True-False-False] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-sh-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-fdr_gbs-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_issorted[s] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-fdr_n-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-s-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-fdr_i-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-h-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-h-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-h-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-s-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-s-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-h-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-fdr_n-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-fdr_tsbky-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-fdr_i-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-fdr_tsbh-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-fdr_tsbky-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-fdr_gbs-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-fdr_tsbky-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-hs-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-b-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-fdr_tsbh-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-sh-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-hommel-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-fdr_tsbky-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-hommel-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-h-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-fdr_gbs-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-fdr_gbs-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-s-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-s-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_fdrcorrection_invalid_method_raises PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-sh-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-hommel-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-h-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-h-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_fdr_twostage PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-hommel-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_floating_precision[fdr_tsbh] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_floating_precision[b] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-hommel-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-sh-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-sh-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-fdr_tsbh-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-fdr_tsbky-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-fdr_i-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-sh-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-b-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-fdr_n-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-hs-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-fdr_tsbky-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_multipletests_empty[ho] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-sh-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-fdr_i-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-sh-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_floating_precision[fdr_gbs] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-fdr_n-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_hommel PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-h-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-h-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-s-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-s-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_null_constrained[False-True-True] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_floating_precision[lfdr] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-fdr_n-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-b-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-sh-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-fdr_i-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-fdr_tsbh-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-sh-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-fdr_gbs-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-fdr_n-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-s-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-s-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-h-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-fdr_i-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-hommel-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-b-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-b-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-hs-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-sh-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-hommel-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-fdr_tsbh-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-hommel-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-fdr_tsbky-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-s-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-fdr_gbs-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-fdr_tsbky-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-hs-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-fdr_gbs-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-hommel-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-sh-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-sh-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-hommel-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-fdr_gbs-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-fdr_gbs-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_issorted[lfdr] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-s-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-s-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-sh-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-h-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-h-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-hommel-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-fdr_tsbky-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-sh-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_issorted[fdr_by] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-fdr_i-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_null_constrained[False-False-True] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-sh-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-fdr_n-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-fdr_tsbh-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-fdr_tsbky-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_floating_precision[ho] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-fdr_tsbky-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-fdr_tsbh-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-fdr_i-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-sh-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-hs-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-b-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-fdr_n-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-hommel-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-fdr_n-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-hommel-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_multipletests_empty[sh] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-fdr_n-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-fdr_i-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_null_distribution PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_floating_precision[s] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-hs-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-fdr_gbs-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-h-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-fdr_tsbh-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-hs-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-fdr_tsbh-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-sh-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-h-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-h-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-h-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-fdr_tsbky-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-s-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-s-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-hs-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_issorted[b] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-hs-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-fdr_tsbh-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_issorted[hs] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-fdr_gbs-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-fdr_tsbky-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-fdr_gbs-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-hs-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-h-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-s-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-s-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-fdr_tsbky-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-fdr_tsbh-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-h-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-h-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_multipletests_empty[h] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-hs-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-hs-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_issorted[fdr_tsbh] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-fdr_n-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-sh-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-fdr_tsbh-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-hommel-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-fdr_i-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-fdr_i-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-hs-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_multipletests_empty[fdr_tsbh] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-fdr_n-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-hs-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-s-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_multipletests_empty[b] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-b-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-b-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-fdr_i-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-fdr_tsbky-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-fdr_n-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-fdr_i-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-b-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-hs-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-fdr_n-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-b-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-fdr_i-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-h-0.01] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-fdr_tsbky-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_issorted[h] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-fdr_gbs-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-s-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-fdr_tsbh-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-fdr_n-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-s-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_null_constrained[True-True-False] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-fdr_tsbky-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-sh-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-fdr_n-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-b-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-fdr_n-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-hs-0.05] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-fdr_i-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_issorted[ho] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-fdr_i-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-fdr_tsbh-0.1] PASSED [ 73%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-fdr_i-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-hs-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-fdr_tsbh-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-b-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-b-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-hs-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_multipletests_empty[fdr_bh] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_null_constrained[True-True-True] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-fdr_tsbh-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-fdr_gbs-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-hs-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-hommel-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-hommel-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-fdr_i-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-sh-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-fdr_tsbky-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-fdr_n-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-hs-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-fdr_n-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_multipletests_empty[fdr_gbs] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-fdr_i-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-s-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-fdr_gbs-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-h-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-fdr_gbs-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-fdr_n-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-fdr_tsbh-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-hommel-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_floating_precision[fdr_by] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-h-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-fdr_tsbky-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-fdr_n-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_null_constrained[False-False-False] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-sh-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-fdr_gbs-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-hommel-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-hommel-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-fdr_gbs-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-h-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-fdr_gbs-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-fdr_tsbky-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-b-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-b-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_multipletests_empty[fdr_tsbky] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-sh-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-hommel-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-hommel-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-h-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-h-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-sh-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-fdr_gbs-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-fdr_tsbh-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-sh-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-b-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-b-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-fdr_i-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-fdr_i-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-fdr_gbs-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_floating_precision[hs] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-fdr_tsbky-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-sh-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-hommel-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-fdr_tsbh-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-fdr_tsbky-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-hommel-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-fdr_tsbh-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-sh-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-s-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_null_constrained[True-False-True] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_multipletests_empty[fdr_by] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-fdr_tsbh-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-fdr_n-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-b-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-s-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-fdr_tsbky-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-fdr_gbs-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-b-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-b-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_floating_precision[fdr_tsbky] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-b-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_floating_precision[h] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-fdr_gbs-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_issorted[sh] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-hommel-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-hommel-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-fdr_gbs-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-fdr_gbs-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-fdr_tsbh-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_issorted[fdr_tsbky] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-sh-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-fdr_tsbh-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_local_fdr PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_multipletests_empty[s] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-sh-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-hommel-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-hommel-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-sh-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-b-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-fdr_tsbky-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-fdr_tsbh-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_multipletests_empty[hs] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-fdr_tsbky-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-sh-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-b-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-b-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-hommel-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-s-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-s-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-fdr_i-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-fdr_i-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-fdr_gbs-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-fdr_tsbky-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-fdr_tsbh-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-hs-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-fdr_n-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-b-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-h-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-fdr_i-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-b-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-b-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-fdr_i-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-fdr_i-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-fdr_n-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-fdr_i-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-fdr_tsbky-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-h-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-h-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-fdr_gbs-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-fdr_tsbh-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-s-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-hs-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-fdr_tsbh-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-fdr_tsbky-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-fdr_tsbh-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_floating_precision[fdr_bh] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-fdr_tsbh-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_tukeyhsd PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[0-b-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-b-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[2-hs-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[4-hs-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-fdr_n-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-s-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-fdr_i-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[9-h-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-fdr_n-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[1-fdr_n-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-fdr_gbs-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-fdr_gbs-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[6-hs-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[8-hommel-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[10-hommel-0.1] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[5-fdr_i-0.01] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[7-fdr_tsbky-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::test_pvalcorrection_reject[3-fdr_n-0.05] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::TestMultiTests4::test_multi_pvalcorrection_rmethods[TSBH_0.05-val7] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::TestMultiTests4::test_multi_pvalcorrection_rmethods[SidakSD-val5] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::TestMultiTests4::test_multi_pvalcorrection PASSED [ 74%] statsmodels/stats/tests/test_multi.py::TestMultiTests4::test_multi_pvalcorrection_rmethods[Bonferroni-val2] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::TestMultiTests4::test_multi_pvalcorrection_rmethods[Hochberg-val3] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::TestMultiTests4::test_multi_pvalcorrection_rmethods[BH-val0] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::TestMultiTests4::test_multi_pvalcorrection_rmethods[Holm-val4] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::TestMultiTests4::test_multi_pvalcorrection_rmethods[SidakSS-val6] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::TestMultiTests4::test_multi_pvalcorrection_rmethods[rawp-val8] PASSED [ 74%] statsmodels/stats/tests/test_multi.py::TestMultiTests4::test_multi_pvalcorrection_rmethods[BY-val1] PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_bse_approx PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_summary PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_aic PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_bic PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_results PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_predict PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_loglike PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_representation PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_params PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_standardized_forecasts_error PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_dynamic_predict PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_bse_oim PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_mle PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_dynamic_predict PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_params PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_bse_approx PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_bse_oim PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_bic PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_aic PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_results PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_standardized_forecasts_error PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_loglike PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_predict PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_mle PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVMA1::test_standardized_forecasts_error PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVMA1::test_bse_oim SKIPPED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVMA1::test_dynamic_predict PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVMA1::test_mle PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVMA1::test_results PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVMA1::test_loglike PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVMA1::test_predict PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVMA1::test_params PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVMA1::test_bic PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVMA1::test_aic PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVMA1::test_bse_approx SKIPPED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_results PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_loglike PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_predict PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_standardized_forecasts_error PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_bse_approx PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_summary PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_mle PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_forecast PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_dynamic_predict PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_bse_oim PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_params PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_aic PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_bic PASSED [ 74%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR2::test_params PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR2::test_mle PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR2::test_bse_approx PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR2::test_bse_oim PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR2::test_bic PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR2::test_aic PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR2::test_standardized_forecasts_error PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR2::test_summary PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR2::test_dynamic_predict PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR2::test_results PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR2::test_predict PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR2::test_loglike PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_summary_after_remove_data PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_extend_results[False-ct] PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_extend_results[False-n] PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_forecast_exog PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_extend_results[True-c] PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_extend_results[True-ct] PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_predict_custom_index PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_param_names_trend PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_misspecifications PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_extend_results[True-n] PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_extend_results_exog PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_apply_results PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_append_results PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_specifications PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_extend_results[False-c] PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_vma1_exog PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_recreate_model PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::test_misc_exog PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog2::test_standardized_forecasts_error PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog2::test_dynamic_predict PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog2::test_results PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog2::test_loglike PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog2::test_predict PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog2::test_mle PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog2::test_forecast PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog2::test_bse_approx PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog2::test_params PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog2::test_bse_oim PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog2::test_aic PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog2::test_bic PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVARMA::test_bse_approx SKIPPED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVARMA::test_dynamic_predict PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVARMA::test_summary PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVARMA::test_aic PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVARMA::test_bic PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVARMA::test_loglike PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVARMA::test_predict PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVARMA::test_results PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVARMA::test_standardized_forecasts_error PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVARMA::test_params PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVARMA::test_mle PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVARMA::test_bse_oim SKIPPED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_params PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_standardized_forecasts_error PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_bse_oim PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_dynamic_predict PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_mle PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_bse_approx PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_loglike PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_predict PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_results PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_summary PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_aic PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_bic PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_dynamic_predict PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_bse_approx PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_bse_oim PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_params PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_mle PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_loglike PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_predict PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_results PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_standardized_forecasts_error PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_bic PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_aic PASSED [ 75%] statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_summary PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother2::test_coef PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother2::test_predict PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother2::test_df PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestKernelSmoother::test_fit_is_a_noop PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestKernelSmoother::test_call_matches_predict PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestKernelSmoother::test_predicted_curve_recovers_quadratic_shape PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestKernelSmoother::test_conf_with_int_subsamples_sorted_x PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestKernelSmoother::test_std_is_sqrt_of_var PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestKernelSmoother::test_predict_scalar_matches_kernel_smooth PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestKernelSmoother::test_predict_array_matches_elementwise_scalar_predict PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestKernelSmoother::test_conf_with_array PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestKernelSmoother::test_default_kernel_is_gaussian PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestKernelSmoother::test_predict_with_non_gaussian_kernel XFAILdocuments accepting any Kernel object via its `Kernel` parameter, but non-Gaussian kernels (e.g., Epanechnikov, Uniform) raise `TypeError: unsupported operand type(s) for -: 'tuple' and 'float'` inside Kernel.smooth() even with default construction (no unusual arguments). Only the default Gaussian kernel currently works. See sandbox.nonparametric.tests.test_kernels for the root-cause investigation.) [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother3::test_df PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother3::test_predict PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother3::test_coef PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother1::test_df PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother1::test_coef PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother1::test_predict PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::test_polysmoother_predict_2d_x_uses_first_column PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::test_polysmoother_call_is_alias_for_predict PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::test_polysmoother_2d_x_in_init_uses_first_row PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::test_polysmoother_gram_is_noop PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::test_polysmoother_fit_weights_none_matches_all_nan PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::test_polysmoother_fit_requires_x_if_never_set PASSED [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::test_polysmoother_fit_2d_x_is_broken XFAILr actually reduces x to 1d (the fix is present but commented out: `# x=x[0,:] # TODO: check orientation, row or col`), unlike the equivalent branches in __init__ and predict() which do perform the reduction (x = x[0, :] / x[:, 0] respectively). Calling fit() with 2d x therefore builds a malformed higher-dimensional self.X and raises LinAlgError from np.linalg.lstsq instead of fitting against one column of x.) [ 75%] statsmodels/sandbox/nonparametric/tests/test_smoothers.py::test_polysmoother_predict_with_no_argument_uses_stored_x PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[2-1] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_plot_acf_kwargs PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[7-12] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[7-2] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_plot_accf_grid PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[1-1] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_plot_quarter PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_plot_acf_missing PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[2-2] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[12-12] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_plot_ccf PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_plot_acf PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[1-2] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_plot_pacf_kwargs PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[7-1] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_predict_plot[0.1-True-model_and_args1] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_plot_pacf_small_sample PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[1-7] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_labels PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_predict_plot[0.1-True-model_and_args0] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[2-7] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_predict_plot[None-True-model_and_args0] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[7-7] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_invalid_subplots PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_predict_plot[None-True-model_and_args1] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[1-12] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_predict_plot[None-False-model_and_args0] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_seasonal_diagnostic_plot PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_plot_predict_passes_alpha_to_conf_int PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[12-2] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_predict_plot[None-False-model_and_args1] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_plot_pccf_irregular_lags PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_predict_plot[0.1-False-model_and_args1] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_plot_pacf PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_plot_pccf PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[12-1] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_predict_plot[0.1-False-model_and_args0] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[2-12] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_plot_month XFAIL [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_plot_pacf_irregular PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_sdp_numbers[12-7] PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_plot_acf_irregular PASSED [ 75%] statsmodels/graphics/tests/test_tsaplots.py::test_seasonal_plot PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_test_corr_weights PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_joint_skew_kurt PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_test_mean PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_ci_kurt PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_ci_skew PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_mv_test_mean PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_test_var_weights PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_mv_test_mean_weights PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_ci_corr PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_ci_skew_weights PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_test_skew PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_test_mean_weights PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_test_kurt PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_test_corr PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_descstat_invalid_input[endog1] PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_descstat_invalid_input[endog0] PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_test_var PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_ci_mean PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::TestDescriptiveStatistics::test_ci_var PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::test_multivariate_namedtuple[mv_test_mean-args0] PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::test_uv_plot_contour PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::test_univariate_namedtuple[test_mean-args0] PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::test_mv_mean_contour PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::test_multivariate_namedtuple[test_corr-args1] PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::test_univariate_namedtuple[test_kurt-args3] PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::test_univariate_namedtuple[test_skew-args2] PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::test_univariate_namedtuple[test_joint_skew_kurt-args4] PASSED [ 75%] statsmodels/emplike/tests/test_descriptive.py::test_univariate_namedtuple[test_var-args1] PASSED [ 75%] statsmodels/stats/tests/test_lilliefors.py::TestLilliefors::test_large_sample PASSED [ 75%] statsmodels/stats/tests/test_lilliefors.py::TestLilliefors::test_pval_bounds PASSED [ 75%] statsmodels/stats/tests/test_lilliefors.py::TestLilliefors::test_x_dims PASSED [ 75%] statsmodels/stats/tests/test_lilliefors.py::TestLilliefors::test_normal PASSED [ 75%] statsmodels/stats/tests/test_lilliefors.py::TestLilliefors::test_min_nobs PASSED [ 75%] statsmodels/stats/tests/test_lilliefors.py::TestLilliefors::test_normal_table PASSED [ 75%] statsmodels/stats/tests/test_lilliefors.py::TestLilliefors::test_expon PASSED [ 75%] statsmodels/stats/tests/test_lilliefors.py::test_get_lilliefors_errors PASSED [ 75%] statsmodels/stats/tests/test_lilliefors.py::test_ksstat PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987SingleComplex::test_pickled_filter SKIPPED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987SingleComplex::test_copied_filter SKIPPED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987SingleComplex::test_loglike SKIPPED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987SingleComplex::test_filtered_state SKIPPED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDouble::test_pickled_filter PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDouble::test_copied_filter PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDouble::test_loglike PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDouble::test_filtered_state PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ForecastDoubleComplex::test_loglike PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ForecastDoubleComplex::test_filtered_state PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Conserve::test_loglike PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Conserve::test_pickled_filter PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Conserve::test_filtered_state PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Conserve::test_copied_filter PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ConserveAll::test_loglike PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ConserveAll::test_filtered_state PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987DoubleComplex::test_pickled_filter PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987DoubleComplex::test_filtered_state PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987DoubleComplex::test_loglike PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987DoubleComplex::test_copied_filter PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989::test_filtered_state PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989::test_loglike PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastConserve::test_pickled_filter PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastConserve::test_loglike PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastConserve::test_copied_filter PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastConserve::test_filtered_state PASSED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Single::test_filtered_state SKIPPED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Single::test_copied_filter SKIPPED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Single::test_loglike SKIPPED [ 75%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Single::test_pickled_filter SKIPPED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::test_prediction_results_clear PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::test_stationary_initialization PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Double::test_copied_filter PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Double::test_filtered_state PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Double::test_loglike PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Double::test_pickled_filter PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ForecastConserve::test_loglike PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ForecastConserve::test_filtered_state PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ConserveAll::test_loglike PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ConserveAll::test_pickled_filter PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ConserveAll::test_filtered_state PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ConserveAll::test_copied_filter PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDoubleComplex::test_pickled_filter PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDoubleComplex::test_loglike PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDoubleComplex::test_copied_filter PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDoubleComplex::test_filtered_state PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ForecastDouble::test_filtered_state PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ForecastDouble::test_loglike PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989Conserve::test_filtered_state PASSED [ 76%] statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989Conserve::test_loglike PASSED [ 76%] statsmodels/tsa/base/tests/test_prediction.py::test_t_test_alternative_deprecated_alias[False-l-larger] PASSED [ 76%] statsmodels/tsa/base/tests/test_prediction.py::test_tvalues[True] PASSED [ 76%] statsmodels/tsa/base/tests/test_prediction.py::test_dist[True-norm] PASSED [ 76%] statsmodels/tsa/base/tests/test_prediction.py::test_t_test_alternative_deprecated_alias[False-s-smaller] PASSED [ 76%] statsmodels/tsa/base/tests/test_prediction.py::test_t_test_invalid_alternative[True] PASSED [ 76%] 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statsmodels/regression/tests/test_robustcov.py::TestClusterJKvsRSandwich::test_wls_vs_r_sandwich[cluster-jk-results_cluster_jk_wls_sandwich_r] PASSED [ 78%] statsmodels/regression/tests/test_robustcov.py::TestClusterJKvsRSandwich::test_r_sandwich_agrees_with_r_summclust PASSED [ 78%] statsmodels/regression/tests/test_robustcov.py::TestClusterJKvsRSandwich::test_ols_vs_r_sandwich[cluster-jk-results_cluster_jk_sandwich_r] PASSED [ 78%] statsmodels/regression/tests/test_robustcov.py::TestClusterJKvsRSandwich::test_ols_vs_r_sandwich[cluster-crv3-results_cluster_crv3_sandwich_r] PASSED [ 78%] statsmodels/regression/tests/test_robustcov.py::TestClusterJKvsRSandwich::test_wls_vs_r_sandwich[cluster-crv3-results_cluster_crv3_wls_sandwich_r] PASSED [ 78%] statsmodels/regression/tests/test_robustcov.py::TestOLSRobust2::test_basic PASSED [ 78%] statsmodels/regression/tests/test_robustcov.py::TestOLSRobust2::test_t_test_summary PASSED [ 78%] 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[ 78%] statsmodels/regression/tests/test_robustcov.py::TestOLSRobustClusterNWPGroupsFit::test_f_test_summary PASSED [ 78%] statsmodels/regression/tests/test_robustcov.py::TestOLSRobustClusterNWPGroupsFit::test_fvalue SKIPPED [ 78%] statsmodels/regression/tests/test_robustcov.py::TestWLSRobustClusterJK::test_hc3_vs_crv3 PASSED [ 78%] statsmodels/regression/tests/test_robustcov.py::TestWLSRobustClusterJK::test_cr3_vs_r PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_stitch_fixed_and_free_params[fixed_lags4-free_lags4-fixed_params4-free_params4-spec_lags4-expected_all_params4] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_package_fixed_and_free_params_info[fixed_params0-spec_ar_lags0-spec_ma_lags0-expected_bunch0] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[1-3-fixed_params2-invalid_fixed_params2] PASSED [ 78%] 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statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_stitch_fixed_and_free_params[fixed_lags2-free_lags2-fixed_params2-free_params2-spec_lags2-expected_all_params2] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_itsmr_with_fixed_params[fixed_params1] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_itsmr_with_fixed_params[fixed_params0] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[2-ma_order0-None-None] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_stitch_fixed_and_free_params[fixed_lags3-free_lags3-fixed_params3-free_params3-spec_lags3-expected_all_params3] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_itsmr_with_fixed_params[fixed_params2] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_set_default_unbiased_with_fixed_params PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_stitch_fixed_and_free_params[fixed_lags1-free_lags1-fixed_params1-free_params1-spec_lags1-expected_all_params1] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[2-2-fixed_params9-None] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_stitch_fixed_and_free_params[fixed_lags0-free_lags0-fixed_params0-free_params0-spec_lags0-expected_all_params0] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_package_fixed_and_free_params_info[fixed_params1-spec_ar_lags1-spec_ma_lags1-expected_bunch1] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[0-2-fixed_params6-None] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[5-ma_order5-fixed_params5-invalid_fixed_params5] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_itsmr PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_set_default_unbiased PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_initial_order PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[ar_order1-0-fixed_params1-None] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_nonconsecutive_lags PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[1-0-fixed_params7-None] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_unbiased_error PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_invalid_orders PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[ar_order8-3-fixed_params8-None] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[ar_order3-ma_order3-fixed_params3-invalid_fixed_params3] PASSED [ 78%] statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_package_fixed_and_free_params_info[fixed_params2-spec_ar_lags2-spec_ma_lags2-expected_bunch2] PASSED [ 78%] statsmodels/stats/tests/test_mediation.py::test_mediation_fit_rng_types[none-parametric] PASSED [ 78%] statsmodels/stats/tests/test_mediation.py::test_mediation_fit_rng_types[none-boot] PASSED [ 78%] statsmodels/stats/tests/test_mediation.py::test_framing_example_moderator_formula PASSED [ 78%] statsmodels/stats/tests/test_mediation.py::test_framing_example_formula PASSED [ 78%] statsmodels/stats/tests/test_mediation.py::test_framing_example_moderator PASSED [ 78%] statsmodels/stats/tests/test_mediation.py::test_surv PASSED [ 78%] statsmodels/stats/tests/test_mediation.py::test_framing_example PASSED [ 78%] statsmodels/stats/tests/test_mediation.py::test_mediation_fit_rng_types[int-boot] PASSED [ 78%] statsmodels/stats/tests/test_mediation.py::test_mediation_boot_rng_reproducible_and_varies PASSED [ 78%] statsmodels/stats/tests/test_mediation.py::test_mediation_fit_rng_types[randomstate-boot] PASSED [ 78%] statsmodels/stats/tests/test_mediation.py::test_mediation_fit_rng_types[generator-parametric] PASSED [ 78%] statsmodels/stats/tests/test_mediation.py::test_mediation_fit_rng_types[randomstate-parametric] PASSED [ 78%] statsmodels/stats/tests/test_mediation.py::test_mediation_fit_rng_types[generator-boot] PASSED [ 78%] statsmodels/stats/tests/test_mediation.py::test_mediation_fit_rng_types[int-parametric] PASSED [ 78%] statsmodels/compat/tests/test_scipy_compat.py::test_next_regular PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[AAN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[MAdA] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[MMA] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[AMdN] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[MNA] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[AMdA] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[MMM] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[AAN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[MNM] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[MAA] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[AMdN] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_keywords PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[AMN] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[MAdA] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[ANN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[MAM] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[MAdN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[MAdM] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[ANN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_seasonal_order[heuristic] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[AMN] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[MAdM] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[AMM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[AAN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[ANM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_prediction_results PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[AMN] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[MMM] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[ANN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[AMdN] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[AAdM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[MNM] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[AAM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[AMN] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[ANN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[AAdM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[MAM] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_estimated_initialization_short_data[9-None-None] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[AAN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_initialization_simple_seasonal_with_trend[add] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[MAdM] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[MAdA] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[ANM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[AMM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[AMdM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_initialization_simple_seasonal_no_trend[False] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[AMM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[ANM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[MAN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[MAdM] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[MAdN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[AMdM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[AAM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[MNN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[AAM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[MMN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[AMdA] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[AAdN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[ANM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[AMdA] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[AAN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[AMM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[MNA] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[MAdN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[MMdA] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[MMA] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[AAM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[MAN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[MMdA] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[ANN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[MAdN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[AMN] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_initialization_heuristic PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[AAM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[MNN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[ANM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[AAdN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[AMdM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[AMdA] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[MMN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[MAA] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[AMM] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[MMdA] SKIPPED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_keywords_warnings PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[MNN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[AAA] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[AAdN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[MMN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[MMN] PASSED [ 78%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[MMdM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_hessian PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[MMdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[AAM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[MNN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[AAdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[ANA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[MMdA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_seasonal_order[estimated] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[MAN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[AMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[MAN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[ANM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[AAdA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[AMM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[MNN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[AMdM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[MMN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[MAM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[MMdA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[MMdM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[AAM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[MAN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[MNM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[MAN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[MMM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[MMdM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[AAdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[AMdM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[MNN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[ANM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[MMN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[AMM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[MAM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[AAdM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[AMN] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[AAdA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[ANN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[MAM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[MMM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[AAdM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[MNM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[MNM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[MMdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[MMdM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[AAN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[MMM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[MAM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[MMN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[MMdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[MAdA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[MNN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[AMN] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[MMM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[AAA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[ANN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[AAdA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[AMdN] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[AAdM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[MNM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[AAdA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[MMM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[MAN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_initialization_known PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[AMdN] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[MNM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[MAM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[AMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[AAN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[ANA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[MAdA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[MMdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[AAA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_initialization_simple_seasonal_with_trend[mul] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[AMdN] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[AMdM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[MNN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[AMdA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_diagnostics_invalid_method_raises PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[MMN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[MAdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[AAA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[AMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_summary_after_remove_data PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_initialization_simple_seasonal_no_trend[None] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[ANA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[MAdA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[ANA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_prediction_results_slow_AAN PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[MAdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[AMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[MAN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[AMdA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[AMdM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[ANA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[AMdA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_seasonal_periods PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[MAM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[AMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[MMdM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_prediction_results_vs_statespace PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_estimated_initialization_short_data[10-None-None] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[AAA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[MNM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[MMdM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[MAdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[MMM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[AAA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[ANA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[AMdM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[AMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[MAdA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[MAA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_ranges PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_aicc_0_dof PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_summary PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[MAM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[MAdM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[AMdM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[AMdN] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[MMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[MNA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_estimated_initialization_short_data[9-add-None] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[MAdM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[MMM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_bounded_fit PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[MNM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[MAA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[MMN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[MAdM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[MMdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[MAdA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[MNN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[AAA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[AMdN] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_estimated_initialization_short_data[10-add-add] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[AAdA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[MAN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[MMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[AMdN] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[AAdA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[MNA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_estimated_initialization_short_data[10-add-None] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[AMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[MAdA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[MMdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[ANA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[MNA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[MMdA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_estimated_initialization_short_data[9-None-add] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[MMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[MMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[AAN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[AAdA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[MNA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[MMdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[AAdM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[AAdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_results_vs_statespace PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[MAA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[AMN] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[MAA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[MMdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[ANN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[AAdA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[MAA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[AMM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_estimated_initialization_short_data[9-add-add] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[ANM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[MAdM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[MMdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[AAdM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[MMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_estimated_initialization_short_data[10-None-add] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[MNA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[MMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[AAM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[AAdA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[MNA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[AAdM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[MAA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[MAdM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_score PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[ANA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[AAdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_model_austouritsts[AAdM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[AMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[ANM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[MMdM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[AMM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[AAA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_simulate_vs_R[MMdA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_prediction_results_slow_AAdA PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_forecast_vs_R[MMdM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[AAM] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[AMdA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[AAdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[ANA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[AAN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[AMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[MAdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[MNA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[MMdA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[MMA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_predict_vs_R[MMdA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_smooth_vs_R[MMdM] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[MAdN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[ANN] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_one_step_ahead[AAA] PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_loglike_vs_R[AMN] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_exact_prediction_intervals PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_convergence_simple PASSED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[AMdA] SKIPPED [ 79%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_residuals_vs_R[MAA] PASSED [ 80%] statsmodels/tsa/tests/test_exponential_smoothing.py::test_fit_vs_R[AAdN] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_varmax[c-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_dfm_mq PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[True-True-n-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[False-True-t-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_varmax[c-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[False-True-t-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[True-False-n-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[True-True-c-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[False-True-c-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[False-False-t-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_varmax[t-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[True-False-c-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[True-True-n-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[True-False-n-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_varmax[n-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[False-False-n-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[False-False-n-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[False-False-t-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[True-False-t-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_TVSS[True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[False-True-c-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[True-True-t-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_varmax[t-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_varmax[n-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[False-True-n-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[False-False-c-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_TVSS[False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[True-True-t-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[False-True-n-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[True-False-c-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[False-False-c-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[True-False-t-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_decompose.py::test_smoothed_decomposition_sarimax[True-True-c-False] PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestPartialResidualPlot::test_partial_residual_poisson PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestAddedVariablePlot::test_added_variable_poisson PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestAddedVariablePlot::test_added_variable_ols PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestCERESPlot::test_ceres_poisson PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestPlotFormula::test_plot_oth PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestPlotFormula::test_plot_influence PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestPlotFormula::test_one_column_exog PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestPlotFormula::test_plot_fit PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestPlotFormula::test_plot_leverage_resid2 PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestABLine::test_abline_remove PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestABLine::test_abline_ab_ax PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestABLine::test_abline_ab PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestABLine::test_abline_model PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestABLine::test_abline_model_ax PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::test_partregress_formula_env PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::test_plot_partregress_result_object PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::test_add_ellipse_and_lowess PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestPlotPandas::test_plot_leverage_resid2 PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestPlotPandas::test_plot_oth PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestPlotPandas::test_plot_fit PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestPlotPandas::test_plot_influence PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestABLinePandas::test_abline_ab PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestABLinePandas::test_abline_model PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestABLinePandas::test_abline_ab_ax PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestABLinePandas::test_abline_model_ax PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestABLinePandas::test_abline_remove PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestPlot::test_plot_influence PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestPlot::test_plot_oth PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestPlot::test_plot_leverage_resid2 PASSED [ 80%] statsmodels/graphics/tests/test_regressionplots.py::TestPlot::test_plot_fit PASSED [ 80%] statsmodels/tools/tests/test_docstring_helpers.py::test_indent_none_or_empty_returns_empty_string PASSED [ 80%] statsmodels/tools/tests/test_docstring_helpers.py::test_substitution_update_dict_params PASSED [ 80%] statsmodels/tools/tests/test_docstring_helpers.py::test_indent_single_line_unchanged PASSED [ 80%] statsmodels/tools/tests/test_docstring_helpers.py::test_substitution_update_noop_for_positional_params PASSED [ 80%] statsmodels/tools/tests/test_docstring_helpers.py::test_indent_multiline PASSED [ 80%] statsmodels/tools/tests/test_docstring_helpers.py::test_indent_non_string_returns_empty_string PASSED [ 80%] statsmodels/tests/test_package.py::test_docstring_optimization_compat PASSED [ 80%] statsmodels/tests/test_package.py::test_test_exit_true_calls_sys_exit PASSED [ 80%] statsmodels/tests/test_package.py::test_lazy_imports PASSED [ 80%] statsmodels/tests/test_package.py::test_test_default_args_and_failure_status PASSED [ 80%] statsmodels/tests/test_package.py::test_test_builds_pytest_command_and_reports_success PASSED [ 80%] statsmodels/stats/tests/test_diagnostic_other.py::TestCMTOLS::test_scorehc0 PASSED [ 80%] statsmodels/stats/tests/test_diagnostic_other.py::TestCMTOLS::test_scoreopg PASSED [ 80%] statsmodels/stats/tests/test_diagnostic_other.py::TestCMTOLS::test_score PASSED [ 80%] statsmodels/stats/tests/test_diagnostic_other.py::test_conditional_moment_test_generic_invalid_cov_type_raises PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_range PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_flat[True] PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_options PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_iter_0_3 PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_delta_rdef PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_frac_2_3 PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_spike PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_exog_predict PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_frac_1_5 PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_delta_0 PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_iter_0 PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_simple PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_duplicate_xs PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_delta_1 PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_import PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_flat[False] PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::test_xvals_dtype PASSED [ 80%] statsmodels/nonparametric/tests/test_lowess.py::test_returns_inputs PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norm[case2-complex128] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norms_consistent[case2] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norms_consistent[case3] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norm[case1-int] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norms_consistent[case1] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norms_consistent[case0] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norms_consistent[case5] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norms_consistent[case4] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norm[case1-float64] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norms_consistent[case6] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norm[case0-complex128] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norms_consistent[case7] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norm[case0-float64] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norm[case2-float64] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norm[case2-int] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norm[case1-complex128] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norm[case0-int] PASSED [ 80%] statsmodels/robust/tests/test_norms.py::test_norms_consistent[case8] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[3-factor_orders3-1-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[k_factors9-factor_orders9-1-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_news[news_222] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[1-1-1-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_news[news_112] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[1-1-1-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_known[11F] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[1-1-1-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[3-6-1-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[3-6-1-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[1-1-1-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_known[22F] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[1-6-1-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_known[111] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep1[22] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[3-1-1-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_known[221] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[k_factors11-factor_orders11-factor_multiplicities11-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[k_factors11-factor_orders11-factor_multiplicities11-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep1[11] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[k_factors9-factor_orders9-1-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_known[112] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[k_factors8-factor_orders8-1-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[1-6-1-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[3-1-1-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_known[222] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[3-factor_orders7-1-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[k_factors8-factor_orders8-1-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[k_factors10-factor_orders10-factor_multiplicities10-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_known[block_221] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_news[news_block_222] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_known[block_111] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[3-1-1-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep1[block_11] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[1-6-1-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_news[news_block_112] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[k_factors10-factor_orders10-factor_multiplicities10-True] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_known[block_222] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[1-6-1-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_known[block_112] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[3-1-1-False] PASSED [ 80%] statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep1[block_22] PASSED [ 80%] statsmodels/iolib/tests/test_summary_old.py::test_regression_summary XFAIL [ 80%] statsmodels/regression/tests/test_dimred.py::test_sir_regularized_1d PASSED [ 80%] statsmodels/regression/tests/test_dimred.py::test_sir_regularized_2d PASSED [ 80%] statsmodels/regression/tests/test_dimred.py::test_sir_regularized_numdiff PASSED [ 80%] statsmodels/regression/tests/test_dimred.py::test_covreduce PASSED [ 80%] statsmodels/regression/tests/test_dimred.py::test_sir_regularized_slice_n PASSED [ 80%] statsmodels/regression/tests/test_dimred.py::test_poisson PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestGaussian::test PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestGaussian::test2m PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestGaussian::test0 PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestClayton::test0 PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestClayton::test PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestClayton::test2m PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestEVAsymLogistic::test PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestEVAsymLogistic::test2m PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestEVAsymLogistic::test0 PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestEVAsymMixed::test0 PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestEVAsymMixed::test2m PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestEVAsymMixed::test PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestEVHR::test0 PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestEVHR::test2m PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestEVHR::test PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestIndependence::test0 PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestFrank::test2m PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestFrank::test0 PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestFrank::test PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::test_rng_types[None] PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::test_rng_types[rng3] PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::test_rng_types[rng2] PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::test_rng_types[0] PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestGumbel::test2m PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestGumbel::test0 PASSED [ 80%] statsmodels/distributions/copula/tests/test_model.py::TestGumbel::test PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoissonBC::test_zero_collinear SKIPPED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoissonBC::test_ttest_tvalues PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoissonBC::test_fitted SKIPPEDuations.GEEResults'>) [ 80%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoissonBC::test_ftest_pvalues PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoissonBC::test_predict_types PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoissonBC::test_zero_constrained SKIPPED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaPoisson::test_categories PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaPoisson::test_combined PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaRankDeficient::test_interaction_df_less_than_nominal PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaRankDeficient::test_df_rank_adjusted PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaOLS::test_combined PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaOLS::test_categories PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaOLS::test_noformula PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestTTestPairwiseOLS3::test_default PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestGenericOLS::test_fitted PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestGenericOLS::test_ttest_tvalues PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestGenericOLS::test_ftest_pvalues PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestGenericOLS::test_zero_constrained PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestGenericOLS::test_zero_collinear PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestGenericOLS::test_predict_types PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestTTestPairwiseOLS2::test_default PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestGenericWLS::test_zero_collinear PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestGenericWLS::test_ttest_tvalues PASSED [ 80%] statsmodels/base/tests/test_generic_methods.py::TestGenericWLS::test_ftest_pvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericWLS::test_zero_constrained PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericWLS::test_fitted PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericWLS::test_predict_types PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaOLSF::test_predict_missing PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaOLSF::test_categories PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaOLSF::test_combined PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericLogit::test_ftest_pvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericLogit::test_ttest_tvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericLogit::test_fitted SKIPPEDults'>) [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericLogit::test_predict_types PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericLogit::test_zero_collinear PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericLogit::test_zero_constrained PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestTTestPairwisePoisson::test_default PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericOLSOneExog::test_fitted PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericOLSOneExog::test_predict_types PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericOLSOneExog::test_zero_collinear PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericOLSOneExog::test_zero_constrained SKIPPED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericOLSOneExog::test_ttest_tvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericOLSOneExog::test_ftest_pvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestTTestPairwiseOLS::test_default PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestTTestPairwiseOLS::test_alpha PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaNegBin::test_combined PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaNegBin::test_categories PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaNegBin1::test_categories PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaNegBin1::test_combined PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestTTestPairwiseOLS4::test_default PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericRLM::test_ttest_tvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericRLM::test_zero_constrained PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericRLM::test_fitted PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericRLM::test_ftest_pvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericRLM::test_zero_collinear PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericRLM::test_predict_types PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_predict_types PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_zero_collinear PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_ttest_tvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_ftest_pvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_fitted SKIPPEDBinomialResults'>) [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_zero_constrained PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGLM::test_zero_collinear PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGLM::test_zero_constrained PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGLM::test_predict_types PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGLM::test_ttest_tvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGLM::test_fitted SKIPPEDGLMResults'>) [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGLM::test_ftest_pvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoisson::test_zero_constrained SKIPPED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoisson::test_predict_types PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoisson::test_fitted SKIPPEDuations.GEEResults'>) [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoisson::test_ftest_pvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoisson::test_zero_collinear SKIPPED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoisson::test_ttest_tvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::test_ttest_tvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaGLM::test_categories PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestWaldAnovaGLM::test_combined PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoissonNaive::test_zero_constrained SKIPPED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoissonNaive::test_predict_types PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoissonNaive::test_fitted SKIPPEDuations.GEEResults'>) [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoissonNaive::test_ttest_tvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoissonNaive::test_ftest_pvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGEEPoissonNaive::test_zero_collinear SKIPPED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_ftest_pvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_zero_collinear PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_ttest_tvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_predict_types PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_zero_constrained PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_fitted SKIPPEDGLMResults'>) [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericPoisson::test_zero_constrained PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericPoisson::test_ttest_tvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericPoisson::test_ftest_pvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericPoisson::test_fitted SKIPPEDesults'>) [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericPoisson::test_predict_types PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericPoisson::test_zero_collinear PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_predict_types PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_zero_collinear PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_ftest_pvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_ttest_tvalues PASSED [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_fitted SKIPPEDesults'>) [ 81%] statsmodels/base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_zero_constrained PASSED [ 81%] statsmodels/graphics/tests/test_dotplot.py::test_invalid_show_names_raises PASSED [ 81%] statsmodels/graphics/tests/test_dotplot.py::test_all PASSED [ 81%] statsmodels/multivariate/tests/test_cancorr.py::test_cancorr PASSED [ 81%] statsmodels/tsa/statespace/tests/test_pickle.py::test_kalman_filter_pickle PASSED [ 81%] statsmodels/tsa/statespace/tests/test_pickle.py::test_pickle_fit_sarimax PASSED [ 81%] statsmodels/tsa/statespace/tests/test_pickle.py::test_representation_pickle PASSED [ 81%] statsmodels/tsa/statespace/tests/test_pickle.py::test_unobserved_components_pickle PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_forecasts PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_simulation_smoothed_state_disturbance PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_smoothed_state_disturbance PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_forecasts_error PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_filtered_state PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_forecasts_error_cov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_using_collapsed PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_smoothed_states_autocov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_filtered_state_cov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_predicted_state_cov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_smoothed_measurement_disturbance_cov SKIPPED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_smoothed_state_disturbance_cov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_smoothed_states_cov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_simulation_smoothed_measurement_disturbance PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_predicted_state PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_smoothed_measurement_disturbance PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_loglike PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_simulation_smoothed_state PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_smoothed_states PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_loglike PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_using_collapsed PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_smoothed_states_autocov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_forecasts_error PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_predicted_state_cov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_smoothed_states_cov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_filtered_state PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_smoothed_measurement_disturbance SKIPPED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_forecasts_error_cov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_smoothed_states PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_smoothed_state_disturbance PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_simulation_smoothed_state_disturbance PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_predicted_state PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_forecasts PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_filtered_state_cov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_simulation_smoothed_state PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_simulation_smoothed_measurement_disturbance PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_smoothed_measurement_disturbance_cov SKIPPED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_smoothed_state_disturbance_cov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissingAlternate::test_simulation_smoothed_state_disturbance PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissingAlternate::test_loglike PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissingAlternate::test_predicted_state_cov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissingAlternate::test_smoothed_measurement_disturbance_cov SKIPPED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissingAlternate::test_smoothed_states_cov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissingAlternate::test_smoothed_states PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissingAlternate::test_filtered_state_cov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissingAlternate::test_predicted_state PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissingAlternate::test_smoothed_state_disturbance_cov PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissingAlternate::test_simulation_smoothed_measurement_disturbance PASSED [ 81%] statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissingAlternate::test_forecasts 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statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_fixed_params_both PASSED [ 84%] statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_misc PASSED [ 84%] statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_statespace_nonconsecutive PASSED [ 84%] statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_statespace_seasonal PASSED [ 84%] statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_fixed_params_no_fixed PASSED [ 84%] statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_ma_itsmr PASSED [ 84%] statsmodels/distributions/tests/test_edgeworth.py::TestCumulants::test_chi2 PASSED [ 84%] statsmodels/distributions/tests/test_edgeworth.py::TestCumulants::test_badvalues PASSED [ 84%] statsmodels/distributions/tests/test_edgeworth.py::TestCumulants::test_norm PASSED [ 84%] statsmodels/distributions/tests/test_edgeworth.py::TestExpandedNormal::test_pdf_no_roots PASSED [ 84%] statsmodels/distributions/tests/test_edgeworth.py::TestExpandedNormal::test_pdf_has_roots PASSED [ 84%] statsmodels/distributions/tests/test_edgeworth.py::TestExpandedNormal::test_chi2_moments PASSED [ 84%] statsmodels/distributions/tests/test_edgeworth.py::TestExpandedNormal::test_coefficients PASSED [ 84%] statsmodels/distributions/tests/test_edgeworth.py::TestExpandedNormal::test_normal PASSED [ 84%] statsmodels/distributions/tests/test_edgeworth.py::TestExpandedNormal::test_too_few_cumulants PASSED [ 84%] statsmodels/distributions/tests/test_edgeworth.py::TestFaaDiBruno::test_neg_arg PASSED [ 84%] statsmodels/distributions/tests/test_edgeworth.py::TestFaaDiBruno::test_small_vals PASSED [ 84%] statsmodels/iolib/tests/test_table_econpy.py::TestCell::test_celldata PASSED [ 84%] statsmodels/iolib/tests/test_table_econpy.py::TestSimpleTable::test_html_fmt1 PASSED [ 84%] statsmodels/iolib/tests/test_table_econpy.py::TestSimpleTable::test_txt_fmt1 PASSED [ 84%] statsmodels/iolib/tests/test_table_econpy.py::TestSimpleTable::test_ltx_fmt1 PASSED [ 84%] statsmodels/iolib/tests/test_table_econpy.py::TestSimpleTable::test_customlabel PASSED [ 84%] statsmodels/stats/tests/test_regularized_covariance.py::test_calc_nodewise_row PASSED [ 84%] statsmodels/stats/tests/test_regularized_covariance.py::test_fit PASSED [ 84%] statsmodels/stats/tests/test_regularized_covariance.py::test_calc_nodewise_weight PASSED [ 84%] statsmodels/stats/tests/test_regularized_covariance.py::test_calc_approx_inv_cov PASSED [ 84%] statsmodels/sandbox/distributions/tests/test_extras.py::TestMvstdnormcdf::test_mvnormcdf_matches_mvstdnormcdf_when_standardized SKIPPED [ 84%] statsmodels/sandbox/distributions/tests/test_extras.py::TestMvstdnormcdf::test_mvstdnormcdf_matches_docstring_example SKIPPED [ 84%] statsmodels/sandbox/distributions/tests/test_extras.py::TestMvstdnormcdf::test_mvnormcdf_rescales_for_nonunit_variance SKIPPED [ 84%] statsmodels/sandbox/distributions/tests/test_extras.py::TestNormExpanGen::test_invalid_mode_raises PASSED [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::TestNormExpanGen::test_centmom_mode_matches_mvsk_mode PASSED [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_acskewt_rvs XFAIL, alpha) does not accept the `size` keyword argument scipy passes to _rvs, so ACSkewT_gen().rvs(...) always raises TypeError.) [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_pdf_mvsk_matches_pdf_moments PASSED [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_pdf_moments_reduces_to_normal_for_zero_skew_kurt PASSED [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_skewt PASSED [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_skewnorm PASSED [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_pdf_moments_requires_at_least_two_moments PASSED [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_pdf_moments_st_is_broken XFAILIn Python 3 `/` is true division, so this always passes a float to range(), which raises TypeError immediately for any call with >= 3 moments (the only case that reaches the loop). Even if that were fixed with `//`, the very next statement is an unconditional bare `raise SystemError`, so the function cannot currently produce a result either way; pdf_moments/pdf_mvsk are the intended non-broken replacements per this module's own docstring.) [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_skewnorm_rvs XFAIL argument that scipy.stats.rv_continuous.rvs() always passes to _rvs on modern scipy (it instead relies on the legacy self._size instance attribute set before calling _rvs). skewnorm.rvs(...) therefore always raises TypeError.) [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_pdf_mvsk_requires_four_moments PASSED [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_get_u_argskwargs PASSED [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_logtransf_gen_default_lower_bound_clips_negative_support PASSED [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_get_u_argskwargs_u_args_is_silently_dropped XFAILore* trying to pop 'u_args' back out: `u_kwargs = {k.replace('u_', '', 1): v for k, v in kwargs.items() if k.startswith('u_')}` renames a passed `u_args=...` to key 'args', then `u_kwargs.pop('u_args', None)` looks for a key that no longer exists (it's 'args' now), so it always returns the None default. A caller's u_args value is silently lost, and a stray 'args' key leaks into u_kwargs instead of being removed.) [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_transf_gen_lognormalg_matches_underlying_distribution PASSED [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_transf_gen_loggammaexpg XFAILant to be called as loggammaexpg.cdf(x, a) for gamma shape parameter `a`, mirroring lognormalg's usage. But Transf_gen._cdf(self, x, *args, **kwargs) does not receive the shape argument by the time it calls self.kls._cdf(self.funcinv(x), *args, **kwargs) -- args is empty -- so stats.gamma._cdf() always raises TypeError for a missing required `a` argument.) [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_transf_gen_invdnormalg_cdf_ppf_roundtrip PASSED [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_exptransf_gen_matches_underlying_distribution PASSED [ 85%] statsmodels/sandbox/distributions/tests/test_extras.py::test_logtransf_gen_matches_underlying_distribution PASSED [ 85%] statsmodels/base/tests/test_constraints.py::TestTransformRestriction::test_homogeneous_restriction_with_forced_zero_solution PASSED [ 85%] statsmodels/base/tests/test_constraints.py::TestTransformRestriction::test_infeasible_restriction_raises PASSED [ 85%] statsmodels/base/tests/test_constraints.py::TestTransformRestriction::test_expand_satisfies_constraint PASSED [ 85%] statsmodels/base/tests/test_constraints.py::TestTransformRestriction::test_expand_reduce_roundtrip PASSED [ 85%] statsmodels/base/tests/test_constraints.py::test_transform_restriction_matches_direct_constrained_ols PASSED [ 85%] statsmodels/tools/tests/test_print_version.py::test_show_versions_show_dirs_false_does_not_print_full_listing PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained2b::test_basic_method PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained2b::test_basic PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained2b::test_other PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained1b::test_basic_method PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained1b::test_other PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained1b::test_basic PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestLogitConstrained1::test_glm SKIPPED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestLogitConstrained1::test_basic PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestLogitConstrained1::test_basic_method PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestLogitConstrained1::test_other PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMPoissonConstrained1b::test_other PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMPoissonConstrained1b::test_basic_method PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMPoissonConstrained1b::test_basic PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMPoissonConstrained1b::test_compare_glm_poisson PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonNoConstrained::test_basic_method PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonNoConstrained::test_other PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonNoConstrained::test_basic PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained2::test_basic_method PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained2::test_summary PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained2::test_predict PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained2::test_fit_constrained_wrap PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained2::test_summary2 PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained2::test_other PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained2::test_glm PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained2::test_basic PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained2HC::test_basic PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained2HC::test_other PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained2HC::test_glm PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained2HC::test_basic_method PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained1c::test_basic PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained1c::test_basic_method PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained1c::test_other PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained2c::test_other PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained2c::test_basic_method PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained2c::test_basic PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained2a::test_basic PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained2a::test_other PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained2a::test_basic_method PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMPoissonConstrained1a::test_other PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMPoissonConstrained1a::test_basic_method PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMPoissonConstrained1a::test_basic PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained1a::test_other PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained1a::test_summary2 PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained1a::test_basic PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained1a::test_summary PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestPoissonConstrained1a::test_basic_method PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained1::test_other PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained1::test_basic PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained1::test_glm PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestGLMLogitConstrained1::test_basic_method PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestLogitConstrained2HC::test_other PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestLogitConstrained2HC::test_basic PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestLogitConstrained2HC::test_basic_method PASSED [ 85%] statsmodels/discrete/tests/test_constrained.py::TestLogitConstrained2HC::test_glm SKIPPED [ 85%] statsmodels/tools/tests/test_sm_exceptions.py::test_parse_error_is_exception_and_raisable PASSED [ 85%] statsmodels/tools/tests/test_sm_exceptions.py::test_parse_error_str_without_docstring_attr PASSED [ 85%] statsmodels/tools/tests/test_sm_exceptions.py::test_parse_error_str_with_docstring_attr PASSED [ 85%] statsmodels/tsa/statespace/tests/test_save.py::test_sarimax_save_remove_data[order2] PASSED [ 85%] statsmodels/tsa/statespace/tests/test_save.py::test_sarimax_pickle PASSED [ 85%] statsmodels/tsa/statespace/tests/test_save.py::test_sarimax_save_remove_data[order1] PASSED [ 85%] statsmodels/tsa/statespace/tests/test_save.py::test_sarimax_save_remove_data[order0] PASSED [ 85%] statsmodels/tsa/statespace/tests/test_save.py::test_existing_pickle PASSED [ 85%] statsmodels/tsa/statespace/tests/test_save.py::test_sarimax PASSED [ 85%] statsmodels/tsa/statespace/tests/test_save.py::test_structural PASSED [ 85%] statsmodels/tsa/statespace/tests/test_save.py::test_dynamic_factor PASSED [ 85%] statsmodels/tsa/statespace/tests/test_save.py::test_varmax PASSED [ 85%] statsmodels/tsa/statespace/tests/test_save.py::test_dynamic_factor_pickle PASSED [ 85%] statsmodels/tsa/statespace/tests/test_save.py::test_varmax_pickle PASSED [ 85%] statsmodels/tsa/statespace/tests/test_save.py::test_structural_pickle PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test_recursive_split_short_gap_sequence PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test_recursive_split PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test_axes_labeling PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test_mosaic_very_complex PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test_default_arg_index PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test_mosaic_empty_cells PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test_proportion_normalization PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test_missing_category PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test_gap_split PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test_data_conversion PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test_mosaic_simple PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test_false_split PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test__reduce_dict PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test_mosaic PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test_rect_pure_split PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test_rect_deformed_split PASSED [ 85%] statsmodels/graphics/tests/test_mosaicplot.py::test__key_splitting PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_tuning_smoke[case3] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_tuning_biweight PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_eff[case4] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_eff[case5] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_tuning_smoke[case2] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_eff[case7] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_tuning_smoke[case0] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_tuning_smoke[case1] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_eff[case6] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_eff[case3] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_tuning_smoke[case4] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_tuning_smoke[case5] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_eff[case2] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_tuning_smoke[case7] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_eff[case0] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_eff[case1] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_tuning_smoke[case6] PASSED [ 85%] statsmodels/robust/tests/test_tools.py::test_hampel_eff PASSED [ 85%] statsmodels/stats/tests/test_correlation.py::test_kernel_covariance PASSED [ 85%] statsmodels/graphics/tests/test_plot_grids.py::test_scatter_ellipse_matches_covariance PASSED [ 85%] statsmodels/graphics/tests/test_plot_grids.py::test_scatter_ellipse_multiple_variables_and_levels PASSED [ 85%] statsmodels/regression/tests/test_tools.py::TestMinimalWLS::test_equivalence_with_wls[True] PASSED [ 85%] statsmodels/regression/tests/test_tools.py::TestMinimalWLS::test_inf_nan[nan] PASSED [ 85%] statsmodels/regression/tests/test_tools.py::TestMinimalWLS::test_equivalence_with_wls[False] PASSED [ 85%] statsmodels/regression/tests/test_tools.py::TestMinimalWLS::test_inf_nan[inf] PASSED [ 85%] statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_pandas_multivariate_dateindex PASSED [ 85%] statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_pandas_univariate_rangeindex PASSED [ 85%] statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_structural PASSED [ 85%] statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_time_varying_out_of_sample_anchored PASSED [ 85%] statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_varmax PASSED [ 85%] statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_time_varying_out_of_sample PASSED [ 85%] statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_sarimax PASSED [ 85%] statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_pandas_multivariate_rangeindex PASSED [ 85%] statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_pandas_anchor PASSED [ 85%] statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_pandas_univariate_dateindex PASSED [ 85%] statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_time_varying_in_sample PASSED [ 85%] statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_dynamic_factor PASSED [ 85%] statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_time_varying_out_of_sample_anchored_end PASSED [ 85%] statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_time_varying_ssm PASSED [ 85%] statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_time_varying_in_sample_anchored PASSED [ 85%] statsmodels/regression/tests/test_cov.py::test_HC_use PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-False-False-True-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-True-True-False-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-True-True-False-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-False-False-False-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-False-False-True-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-False-False-True-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-True-False-False-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-False-True-False-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_seasonal_alignment[type: dataframe, exponential: False-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-False-True-False-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-False-False-True-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-False-False-False-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-True-False-True-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-True-False-False-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-False-True-False-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_errors[type: series, exponential: False] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-False-True-True-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-True-True-False-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-False-False-False-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-True-True-True-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-False-False-False-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-True-True-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-False-False-False-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-True-False-True-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-True-False-False-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-True-True-True-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-True-True-False-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-True-False-False-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-False-False-True-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-False-False-True-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_errors[type: dataframe, exponential: False] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-True-True-False-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-False-False-False-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-False-False-False-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-True-True-False-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-False-False-True-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-False-True-True-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-False-True-False-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-True-False-True-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-True-True-True-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-False-False-False-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-True-True-True-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-False-True-True-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-True-True-True-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-True-False-True-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-True-False-True-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-False-True-False-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-True-True-True-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-False-True-False-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-False-False-False-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-True-False-False-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-False-False-False-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-True-False-False-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-False-True-True-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-False-True-False-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-False-False-False-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-False-True-True-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-True-False-False-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-True-True-False-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-True-False-False-4] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-True-True-False-None] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-False-True-True-12] PASSED [ 85%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-True-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-False-True-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-False-False-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-False-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-False-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-True-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-True-True-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-False-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-True-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-True-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-True-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-True-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-True-True-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-True-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-False-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-True-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-True-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-True-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-True-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-True-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-True-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-False-True-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-False-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-False-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-True-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-True-True-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-True-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-True-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-True-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-True-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_no_freq PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-True-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-False-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-False-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-True-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-False-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-True-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-True-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-True-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-False-False-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-True-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-True-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-False-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-False-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-False-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-True-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-False-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-False-True-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-False-True-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-True-False-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-True-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-False-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-True-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-False-True-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-False-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-True-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-False-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-True-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-True-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-False-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-False-True-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-False-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-False-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-False-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-False-False-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-False-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-True-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-False-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-True-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-False-True-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-True-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-False-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-False-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-True-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-False-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-True-True-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-True-True-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-True-True-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-True-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-False-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-True-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-False-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-False-False-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-False-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-False-True-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-False-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-True-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-True-False-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-True-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-True-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-True-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-False-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-True-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-False-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-True-True-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-True-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-False-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-True-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-True-True-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-True-True-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-True-True-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-False-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-False-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-True-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-True-True-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-True-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-True-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-False-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-False-True-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-True-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_seasonal_alignment[type: dataframe, exponential: False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-False-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_seasonal_alignment[type: dataframe, exponential: True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-False-True-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-True-True-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-False-False-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-True-True-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-True-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-False-False-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-True-False-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-True-False-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-True-True-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-False-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-True-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-False-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-False-True-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_seasonal_alignment[type: array, exponential: True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-False-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-True-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-True-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-False-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-False-True-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-False-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-True-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-True-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-False-True-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-True-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-False-True-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-True-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-False-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-True-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-False-True-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-False-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-True-True-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-True-False-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-True-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-True-True-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-True-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-False-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-True-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-True-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_errors[type: array, exponential: True] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-False-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-False-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-True-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-True-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-True-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-True-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-False-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-False-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_pi_width PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-False-True-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-False-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-False-True-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-False-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-False-True-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-False-True-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-True-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-True-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-True-True-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-False-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-True-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-True-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-True-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-True-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-False-True-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-False-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-True-True-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-True-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-False-True-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-False-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-True-False-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-True-False-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-True-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-False-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-False-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-True-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-True-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-False-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-True-True-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-True-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-False-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-False-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-False-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-True-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-True-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-False-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-True-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-True-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-True-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-False-True-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-False-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-True-True-True-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-True-False-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-False-True-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-False-True-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-True-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-False-True-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-True-True-False-4] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-False-True-False-None] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-False-False-False-12] PASSED [ 86%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-False-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_seasonal_alignment[type: series, exponential: False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-False-True-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-False-True-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-False-True-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-False-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-False-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-False-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-True-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-True-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-True-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-True-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-True-True-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_seasonal_alignment[type: array, exponential: False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-True-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-False-False-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-True-False-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-True-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-False-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-True-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-False-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-False-True-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-True-False-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-False-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-True-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_seasonal_alignment[type: series, exponential: True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-False-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-True-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-True-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-False-True-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-True-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_seasonal_alignment[type: array, exponential: True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-False-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-True-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-True-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-True-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-True-False-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-True-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-True-False-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-False-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-False-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-False-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-False-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-False-False-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-False-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-False-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-True-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-False-True-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-False-False-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-False-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-True-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-True-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-True-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-False-False-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-True-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-True-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-True-True-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-True-True-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-False-True-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-False-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-False-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-False-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-True-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-False-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-False-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-False-False-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-False-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-True-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-True-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-True-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-True-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-False-False-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-True-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-False-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-True-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-True-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-False-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-True-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-True-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-False-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-False-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-True-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-False-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-False-False-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-True-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-False-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-True-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-True-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-False-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-True-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-False-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-False-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-True-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-True-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-False-True-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-True-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-True-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-False-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-False-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-False-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-True-True-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-False-False-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-False-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-False-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-True-False-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-False-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-True-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-False-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-True-False-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-False-False-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_alt_index[period] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-True-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-True-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-True-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-True-True-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-False-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-True-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-False-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-False-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-True-False-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-True-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-False-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-True-False-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-True-False-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-False-False-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-False-True-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-False-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-True-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-False-True-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-False-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-False-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-False-True-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-True-True-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-True-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-False-True-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-False-False-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-False-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-True-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-True-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-False-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-True-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-True-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-True-False-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-True-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-False-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-True-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-False-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-False-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-False-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-False-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-True-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-True-False-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-True-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-True-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-False-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-False-True-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-True-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-False-True-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-True-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-False-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-True-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-False-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-False-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-False-True-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-False-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-True-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-False-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-False-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-True-True-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-True-True-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-False-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-False-False-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-True-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-False-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-True-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-True-True-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-True-False-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-True-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-True-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-False-True-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-False-True-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-False-True-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-True-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-True-True-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-False-True-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-False-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-False-False-True-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-False-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-False-False-False-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-False-True-True-12] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-True-False-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-True-True-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-True-True-False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-False-False-True-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-False-False-False-None] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_seasonal_alignment[type: array, exponential: False-4] PASSED [ 87%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-False-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-False-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-True-True-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-False-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-True-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-False-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-False-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-True-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-True-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-False-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-True-False-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-True-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-True-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-True-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-False-True-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-True-False-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-False-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-False-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-True-True-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-True-True-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-True-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-True-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-False-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-True-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-True-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-True-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-False-False-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-False-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-False-False-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-True-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-True-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-False-True-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-True-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-False-True-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-False-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-False-True-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-True-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-False-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-True-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_plot_predict PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-False-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-True-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-True-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-False-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-False-True-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-False-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-True-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-True-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-False-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-True-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-True-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-False-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-False-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-True-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-False-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-False-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-True-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-False-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-False-True-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-True-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-False-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-True-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-False-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-True-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-False-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-True-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-False-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-True-True-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-False-True-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-True-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-False-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-True-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-False-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-False-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-False-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-True-False-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-True-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-True-True-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_alt_index[datetime] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-True-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_errors[type: array, exponential: False] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-False-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-False-False-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-True-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-True-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-False-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-False-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-True-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-True-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-False-True-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-True-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-True-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-True-True-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-False-True-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-True-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-False-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-True-True-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-True-True-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-False-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-True-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-False-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-False-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-False-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-False-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-False-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-False-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-True-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-True-False-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-False-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-False-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-True-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-True-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-False-True-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-False-True-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-False-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-False-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_errors[type: dataframe, exponential: True] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-False-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-False-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-False-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-False-True-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-True-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-True-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-False-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-False-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-True-True-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-True-True-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-False-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-True-False-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-True-False-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-False-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-False-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-False-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-True-True-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-True-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-False-False-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-False-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-False-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-True-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-False-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-True-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-True-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-False-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-True-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-True-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-True-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-False-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-False-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-True-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-True-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-True-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-False-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-False-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-True-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-False-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-False-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-True-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-True-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-False-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-False-True-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-False-False-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-False-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-False-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-False-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_seasonal_alignment[type: dataframe, exponential: True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-False-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-True-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-False-False-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-False-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-True-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-True-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-True-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-True-True-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-False-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-False-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-True-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-False-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-True-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-True-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-True-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-False-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-True-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-True-False-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-False-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-False-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-False-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-False-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-True-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-True-True-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-True-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-True-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-False-False-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-False-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-True-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-False-True-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-False-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-True-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-True-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-True-True-True-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-False-False-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-False-False-True-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-True-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-True-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-True-True-False-4] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-True-True-False-None] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_alt_index[range] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-True-False-False-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-False-True-True-12] PASSED [ 88%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_seasonal_alignment[type: series, exponential: True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-False-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-False-False-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-False-False-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-False-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-False-False-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-False-True-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-False-False-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-True-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-False-True-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-False-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-False-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-True-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-False-True-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-True-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-False-False-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-False-False-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-False-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-True-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-False-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-False-False-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_alt_index[nofreq] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-True-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-True-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-False-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-False-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-False-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-False-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-True-False-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-False-False-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-False-False-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-True-False-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-True-True-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-True-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-False-True-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-False-False-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-False-True-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-False-False-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-False-True-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-True-False-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-True-False-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-True-True-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-True-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-True-False-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-False-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-True-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-True-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-True-True-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-False-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-True-False-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-False-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-True-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-True-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-False-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-True-True-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-True-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-False-False-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-True-True-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-True-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-False-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-False-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-True-False-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-False-False-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-True-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-True-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-False-False-True-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-False-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-True-True-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-False-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-True-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-True-True-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-False-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-False-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-True-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-False-False-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-True-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-True-True-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-True-True-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-False-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-False-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-False-False-True-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-True-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-True-False-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-False-False-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-False-True-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-False-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_errors[type: series, exponential: True] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-False-True-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-True-True-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-True-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-False-False-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-False-True-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-True-False-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-True-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-True-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-False-False-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-False-True-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-False-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-False-True-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-additive-True-False-True-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-True-True-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-False-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-False-True-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-False-True-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-False-True-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-False-True-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-False-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-True-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-False-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-True-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_auto PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-True-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-True-True-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-False-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-False-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-False-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-True-True-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_forecast_seasonal_alignment[type: series, exponential: False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-False-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-True-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-False-False-True-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-False-True-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-True-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-True-True-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-True-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-False-True-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-False-True-True-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-False-True-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-True-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-True-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-False-False-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-True-False-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-multiplicative-True-False-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-False-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-True-False-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-additive-False-False-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-False-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-True-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-auto-True-False-True-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-False-True-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-False-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-True-True-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-True-False-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-False-True-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-False-False-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: False-multiplicative-True-False-True-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-True-True-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-True-True-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-True-True-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-True-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-True-False-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-True-True-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-False-True-True-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-False-True-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-multiplicative-True-True-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-True-False-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-True-True-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-False-True-False-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-auto-True-True-False-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-False-False-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-True-False-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-True-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-False-True-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-additive-True-False-False-False-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-True-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-True-False-True-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-auto-False-False-False-True-None] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-True-False-False-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-True-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-additive-False-True-True-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: dataframe, exponential: True-multiplicative-True-True-False-False-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: False-auto-False-False-True-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-multiplicative-False-False-True-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-True-True-False-False-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-additive-False-False-True-True-4] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-additive-False-False-True-True-12] PASSED [ 89%] statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: True-auto-False-True-False-True-12] PASSED [ 89%] 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statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params5-ma_params5-1.123] PASSED [ 90%] statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params1-1-ma_params1-1] PASSED [ 90%] statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params2-ma_params2-1] PASSED [ 90%] statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params3-ma_params3-1] PASSED [ 90%] statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params0-ma_params0-1] PASSED [ 90%] statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params1-ma_params1-1] PASSED [ 90%] statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params0-1-ma_params0-1] PASSED [ 90%] statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params0-ma_params0-1] PASSED [ 90%] statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params1-ma_params1-1] PASSED [ 90%] statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params2-ma_params2-1] PASSED [ 90%] statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params3-ma_params3-1] PASSED [ 90%] statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params5-1-ma_params5-1.123] PASSED [ 90%] statsmodels/robust/tests/test_scale.py::TestHuber::test_huber_result_shape PASSED [ 90%] statsmodels/robust/tests/test_scale.py::TestMad::test_mad_empty PASSED [ 90%] statsmodels/robust/tests/test_scale.py::TestMad::test_mad PASSED [ 90%] statsmodels/robust/tests/test_scale.py::TestMad::test_mad_center PASSED [ 90%] statsmodels/robust/tests/test_scale.py::TestChem::test_mean PASSED [ 90%] statsmodels/robust/tests/test_scale.py::TestChem::test_qn PASSED [ 90%] statsmodels/robust/tests/test_scale.py::TestChem::test_huber_scale PASSED [ 90%] statsmodels/robust/tests/test_scale.py::TestChem::test_median PASSED [ 90%] statsmodels/robust/tests/test_scale.py::TestChem::test_huber_Hampel PASSED [ 90%] statsmodels/robust/tests/test_scale.py::TestChem::test_iqr PASSED [ 90%] statsmodels/robust/tests/test_scale.py::TestChem::test_huber_huberT PASSED [ 90%] statsmodels/robust/tests/test_scale.py::TestChem::test_huber_location PASSED [ 90%] statsmodels/robust/tests/test_scale.py::TestChem::test_mad PASSED [ 90%] statsmodels/robust/tests/test_scale.py::TestQn::test_qn_empty PASSED [ 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statsmodels/tsa/tests/test_arima_process.py::test_arma_generate_sample[ma3-ar1] PASSED [ 90%] statsmodels/tsa/tests/test_arima_process.py::test_armafft[ma0-ar1] PASSED [ 90%] statsmodels/tsa/tests/test_arima_process.py::test_spectrum[ma3-ar2] PASSED [ 90%] statsmodels/tsa/tests/test_arima_process.py::test_spectrum[ma3-ar3] PASSED [ 90%] statsmodels/tsa/tests/test_arima_process.py::test_arma_generate_sample[ma3-ar0] PASSED [ 90%] statsmodels/tsa/tests/test_arima_process.py::test_armafft[ma0-ar0] PASSED [ 90%] statsmodels/tsa/tests/test_arima_process.py::test_arma_acf_compare_R_ARMAacf PASSED [ 90%] statsmodels/tsa/tests/test_arima_process.py::test_spectrum[ma3-ar1] PASSED [ 90%] statsmodels/tsa/tests/test_arima_process.py::test_armafft[ma0-ar2] PASSED [ 90%] statsmodels/tsa/tests/test_arima_process.py::test_arma_generate_sample[ma3-ar2] PASSED [ 90%] statsmodels/tsa/tests/test_arima_process.py::test_armafft[ma0-ar3] PASSED [ 90%] 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[ 90%] statsmodels/tsa/tests/test_arima_process.py::TestArmaProcess::test_from_roots PASSED [ 90%] statsmodels/tsa/tests/test_arima_process.py::TestArmaProcess::test_impulse_response PASSED [ 90%] statsmodels/tsa/tests/test_arima_process.py::TestArmaProcess::test_arma2ar PASSED [ 90%] statsmodels/tsa/tests/test_arima_process.py::TestArmaProcess::test_from_coeff PASSED [ 90%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-True-False-False] PASSED [ 90%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_invalid_fittedvalues_resid_predict PASSED [ 90%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_low_memory_fit PASSED [ 90%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate[True-False] PASSED [ 90%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-False-True-False] PASSED [ 90%] 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PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-True-False-True] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-False-False-True] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-False-False-True] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-False-True-True] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-True-True-False] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate_extra[False-False-False] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_fittedvalues_resid_predict[510] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-False-False-True] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate_extra[True-False-False] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate_extra[False-True-False] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-True-True] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate[True-True] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-True-False] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-False-False-False] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-False-False-False] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-True-False] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_get_prediction_memory_conserve PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-False-True-True] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate_extra[False-False-True] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-True-True-True] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-False-False] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-False-True-False] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_fit PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate_extra[False-True-True] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-False-True] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-False-True-True] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate[False-False] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_low_memory_filter PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-False-True] PASSED [ 91%] statsmodels/tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-True-True] PASSED [ 91%] statsmodels/discrete/tests/test_diagnostic.py::TestCountDiagnostic::test_count PASSED [ 91%] statsmodels/discrete/tests/test_diagnostic.py::TestCountDiagnostic::test_probs PASSED [ 91%] statsmodels/discrete/tests/test_diagnostic.py::TestPoissonDiagnosticClass::test_spec_tests PASSED [ 91%] statsmodels/sandbox/regression/tests/test_predstd.py::TestWlsPredictionStd::test_explicit_exog_matches_default_subset PASSED [ 91%] statsmodels/sandbox/regression/tests/test_predstd.py::TestWlsPredictionStd::test_narrower_alpha_gives_wider_interval PASSED [ 91%] statsmodels/sandbox/regression/tests/test_predstd.py::TestWlsPredictionStd::test_explicit_weights_with_explicit_exog PASSED [ 91%] statsmodels/sandbox/regression/tests/test_predstd.py::TestWlsPredictionStd::test_weights_shape_mismatch_raises PASSED [ 91%] statsmodels/sandbox/regression/tests/test_predstd.py::TestWlsPredictionStd::test_default_exog_matches_nobs PASSED [ 91%] statsmodels/sandbox/regression/tests/test_predstd.py::TestWlsPredictionStd::test_scalar_weight_with_explicit_exog PASSED [ 91%] statsmodels/sandbox/regression/tests/test_predstd.py::TestWlsPredictionStd::test_wrong_exog_shape_raises PASSED [ 91%] statsmodels/sandbox/regression/tests/test_predstd.py::TestWlsPredictionStd::test_wls_default_exog_matches_nobs PASSED [ 91%] statsmodels/sandbox/regression/tests/test_predstd.py::TestAtleast2dcol::test_accepts_plain_list PASSED [ 91%] statsmodels/sandbox/regression/tests/test_predstd.py::TestAtleast2dcol::test_1d_becomes_column PASSED [ 91%] statsmodels/sandbox/regression/tests/test_predstd.py::TestAtleast2dcol::test_0d_becomes_2d PASSED [ 91%] statsmodels/sandbox/regression/tests/test_predstd.py::TestAtleast2dcol::test_2d_input_raises PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_select_order PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_plot PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_forecast_interval PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_acf_2_lags PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_stderr PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_acorr PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_causality_no_lags PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_hqic PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_tstat PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_acf PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_fevd_plot PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_plot_acorr PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_fevd_cov PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_get_eq_index PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_ma_rep PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_is_stable PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_causality PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_cov_ybar PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_names PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_nobs PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_repr PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_plot_figsizes PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_summary PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_pvalues PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_cov_params PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_lagorder_select PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_fpe PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_plot_forecast PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_bic PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_constructor PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_aic PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_params PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_plot_cum_effects PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_fevd_repr PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_loglike PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_reorder PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_plot_irf PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_irf_coefs PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_fevd_summary PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_forecast PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_detsig PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResults::test_plot_sim PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARExtras::test_simulate_var_int_seed_warns_consistently PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARExtras::test_forecast_cov PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARExtras::test_process_plotting PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARExtras::test_exog PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARExtras::test_multiple_simulations PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARExtras::test_process PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_pickle PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_lutkepohl_parse PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_var_fit_valid_trend[c-1] PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_var_constant PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_irf_trend PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_var_trend PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_var_fit_invalid_trend_raises PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_get_trendorder PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_var_fit_valid_trend[ctt-3] PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_var_fit_valid_trend[ct-2] PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_var_fit_valid_trend[n-0] PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_irf_plot_err_bands_kwarg PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_irf_err_bands PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_0_lag PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_irf_resim_replications_differ[randomstate] PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_irf_resim_replications_differ[generator] PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_correct_nobs PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_var_maxlag PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_varprocess_plot_acorr PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_var_cov_params_pandas PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_plot_sample_acorr PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_sample_acov PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_from_formula PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_forecast_wrong_shape_params PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_irf_invalid_stderr_type_raises PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_sample_acorr PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_whiteness_nlag PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_irf_resim_replications_differ[int] PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_irf_resim_reproducible_with_int_seed PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_var_model_predict_matches_forecast_and_fittedvalues PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::test_summaries_exog PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResultsLutkepohl::test_cum_irf_stderr PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResultsLutkepohl::test_lr_effect_stderr PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResultsLutkepohl::test_approx_mse PASSED [ 91%] statsmodels/tsa/vector_ar/tests/test_var.py::TestVARResultsLutkepohl::test_irf_stderr PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_legacy_orderer[y ~ 1 + C(f):C(d):a + C(d):a + c + a:b + C(e):b + C(f):a + a + C(d) + b +C(f):C(d) + C(d):C(e) + C(f)] SKIPPED [ 91%] statsmodels/formula/tests/test_manager.py::test_default_value PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_model_spec[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_formula_manager_no_formulaic PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_engine_options_order[none] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_empty_eval_patsy PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_engine_options_engine[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_engine_options_order[degree] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_factor_categories[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_intercept_idx[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_description[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_legacy_orderer[y ~ 1 + C(e) + C(f):C(e) + a + a:b + C(d):a:b + b + C(d)] SKIPPED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_term_name_alt[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_legacy_orderer[y ~ a - 1] SKIPPED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_linear_constraints[patsy-x + z = 1] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_linear_constraints[patsy-constraint0] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_slice[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_legacy_orderer[y ~ 1 + C(d):a + b + a + C(e)] SKIPPED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_linear_constraints[patsy-constraint1] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_engine_options_order_effect SKIPPED [ 91%] statsmodels/formula/tests/test_manager.py::test_legacy_orderer[y ~ d:f:c:b + C(f):c:b + a:b + a + C(d):a:b + c:b + b + C(d) + C(e) + C(f):C(e) - 1] SKIPPED [ 91%] statsmodels/formula/tests/test_manager.py::test_formula_manager_no_patsy SKIPPED [ 91%] statsmodels/formula/tests/test_manager.py::test_legacy_orderer[y ~ a + C(d):a:b + a:b + b + C(d) + C(e) + C(f):C(e) - 1] SKIPPED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_linear_constraints[patsy-constraint3] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_column_names[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_empty_eval_patsy_errors PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_spec[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_single_array[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_contrast_matrix[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_linear_constraints[patsy-constraint2] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_term_name_slices_alt[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_legacy_orderer[y ~ 1 + a + C(e) + a:C(e) + C(f)] SKIPPED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_term_name[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_term_name_slices[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_legacy_orderer[y ~ a + C(e) + a:C(e) + C(f) + C(f):C(d) - 1] SKIPPED [ 91%] statsmodels/formula/tests/test_manager.py::test_engine[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_engine_options_err PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_engine_options_order[legacy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_legacy_orderer[y ~ a + C(e) + a:C(e) + C(f) - 1] SKIPPED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_empty_eval_formulaic SKIPPED [ 91%] statsmodels/formula/tests/test_manager.py::test_na_action[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_legacy_orderer[y ~ a + C(e) - 1] SKIPPED [ 91%] statsmodels/formula/tests/test_manager.py::test_engine_options_order[sort] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_legacy_orderer[y ~ 1 + a + C(e) + a:C(e) + C(f) + C(f):C(d)] SKIPPED [ 91%] statsmodels/formula/tests/test_manager.py::test_has_intercept[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_remove_intercept[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_bad_constraint[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_get_na_action[patsy] PASSED [ 91%] statsmodels/formula/tests/test_manager.py::test_two_arrays[patsy] PASSED [ 91%] statsmodels/tsa/base/tests/test_datetools.py::test_dates_from_range PASSED [ 91%] statsmodels/tsa/base/tests/test_datetools.py::test_regex_matching_quarter PASSED [ 91%] statsmodels/tsa/base/tests/test_datetools.py::test_regex_matching_month PASSED [ 91%] statsmodels/genmod/tests/test_gee_glm.py::TestCompareGamma::test_resid PASSED [ 91%] statsmodels/genmod/tests/test_gee_glm.py::TestCompareGamma::test_basic PASSED [ 91%] statsmodels/genmod/tests/test_gee_glm.py::TestComparePoisson::test_basic PASSED [ 91%] statsmodels/genmod/tests/test_gee_glm.py::TestComparePoisson::test_resid PASSED [ 91%] statsmodels/genmod/tests/test_gee_glm.py::TestCompareLogit::test_basic PASSED [ 91%] statsmodels/genmod/tests/test_gee_glm.py::TestCompareLogit::test_resid PASSED [ 91%] statsmodels/genmod/tests/test_gee_glm.py::TestCompareGaussian::test_basic PASSED [ 91%] statsmodels/genmod/tests/test_gee_glm.py::TestCompareGaussian::test_resid PASSED [ 91%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWEpa::test_evaluate PASSED [ 91%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWEpa::test_kernel_constants PASSED [ 91%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWEpa::test_density XFAIL [ 91%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWEpa::test_compare PASSED [ 91%] statsmodels/nonparametric/tests/test_kde.py::TestKdeWeights::test_density PASSED [ 91%] statsmodels/nonparametric/tests/test_kde.py::TestKdeWeights::test_evaluate PASSED [ 91%] statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussFFT::test_density PASSED [ 91%] statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussFFT::test_evaluate PASSED [ 91%] statsmodels/nonparametric/tests/test_kde.py::TestKDEExceptions::test_wrong_weight_length_exception PASSED [ 91%] statsmodels/nonparametric/tests/test_kde.py::TestKDEExceptions::test_check_is_fit_exception PASSED [ 91%] statsmodels/nonparametric/tests/test_kde.py::TestKDEExceptions::test_non_weighted_fft_exception PASSED [ 91%] statsmodels/nonparametric/tests/test_kde.py::TestKDEExceptions::test_non_gaussian_fft_exception PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWTri::test_compare PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWTri::test_kernel_constants PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWTri::test_density XFAIL [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWTri::test_evaluate PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos::test_kernel_constants PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos::test_density XFAIL [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos::test_evaluate SKIPPED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos::test_compare PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussPandas::test_evaluate PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussPandas::test_icdf_gridded PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussPandas::test_sf_gridded PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussPandas::test_density PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussPandas::test_cdf_gridded PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussPandas::test_support_gridded PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEEpanechnikov::test_evaluate PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEEpanechnikov::test_density PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWBiw::test_evaluate PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWBiw::test_compare PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWBiw::test_density XFAIL [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWBiw::test_kernel_constants PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos2::test_density XFAIL [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos2::test_compare PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos2::test_kernel_constants PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos2::test_evaluate PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::test_kde_bw_positive PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::test_fit_self PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::test_entropy_infinite_domain_kernel PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::test_entropy_finite_domain_kernel[epa] PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::test_kdensity_result_object_true[kdensity] PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::test_entropy_finite_domain_kernel[tri] PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::test_entropy_finite_domain_kernel[cos] PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::test_entropy_finite_domain_kernel[triw] PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::test_kdensity_result_object_default[kdensity] PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::test_entropy_finite_domain_kernel[biw] PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::test_entropy_finite_domain_kernel[uni] PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::test_kdensity_result_object_default[kdensityfft] PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::test_kdensity_result_object_true[kdensityfft] PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDETriangular::test_density PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDETriangular::test_evaluate PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_icdf_gridded PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_density PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_support_gridded PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_sf_gridded PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_evaluate PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_cdf_gridded PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDECustomBandwidth::test_check_is_fit_ok_with_float_bandwidth[False] PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDECustomBandwidth::test_check_is_fit_ok_with_float_bandwidth[True] PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDECustomBandwidth::test_check_is_fit_ok_with_standard_custom_bandwidth PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDECustomBandwidth::test_check_is_fit_ok_with_custom_bandwidth PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWGauss::test_evaluate PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWGauss::test_compare PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWGauss::test_kernel_constants PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEWGauss::test_density XFAIL [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestNormConstant::test_norm_constant_calculation PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEBiweight::test_density PASSED [ 92%] statsmodels/nonparametric/tests/test_kde.py::TestKDEBiweight::test_evaluate PASSED [ 92%] statsmodels/tsa/statespace/tests/test_cfa_tvpvar.py::test_tvpvar PASSED [ 92%] statsmodels/tsa/tests/test_bds.py::TestBDSGDPC1::test_stat PASSED [ 92%] statsmodels/tsa/tests/test_bds.py::TestBDSGDPC1::test_pvalue PASSED [ 92%] statsmodels/tsa/tests/test_bds.py::TestBDSNormal::test_stat PASSED [ 92%] statsmodels/tsa/tests/test_bds.py::TestBDSNormal::test_pvalue PASSED [ 92%] statsmodels/tsa/tests/test_bds.py::TestBDSCombined::test_pvalue PASSED [ 92%] statsmodels/tsa/tests/test_bds.py::TestBDSCombined::test_stat PASSED [ 92%] statsmodels/tsa/tests/test_bds.py::TestBDSSequence::test_stat PASSED [ 92%] statsmodels/tsa/tests/test_bds.py::TestBDSSequence::test_pvalue PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link13-link23-inverse] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_inverse_deriv2 PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link15-link25-deriv] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link13-link23-__call__] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link11-link21-deriv] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink_deriv2_numdiff PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link12-link22-__call__] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_deriv PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link11-link21-inverse_deriv2] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link10-link20-inverse_deriv2] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link11-link21-__call__] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link12-link22-inverse_deriv2] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link13-link23-inverse_deriv2] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link10-link20-deriv2] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link14-link24-inverse_deriv] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link15-link25-inverse_deriv2] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link13-link23-deriv2] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link14-link24-inverse_deriv2] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link12-link22-inverse] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link15-link25-inverse_deriv] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link10-link20-__call__] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link14-link24-deriv] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_invlogit_stability PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link10-link20-deriv] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_inverse PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_inverse_deriv PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link15-link25-deriv2] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link10-link20-inverse_deriv] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link12-link22-deriv] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link15-link25-inverse] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link10-link20-inverse] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link11-link21-inverse_deriv] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link14-link24-deriv2] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link14-link24-inverse] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_deriv2 PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link11-link21-inverse] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link14-link24-__call__] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link13-link23-inverse_deriv] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link12-link22-deriv2] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link12-link22-inverse_deriv] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link15-link25-__call__] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link11-link21-deriv2] PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_link_base_class_placeholders PASSED [ 92%] statsmodels/genmod/families/tests/test_link.py::test_cdflink[link13-link23-deriv] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::TestPHReg::test_formula_args PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::TestPHReg::test_missing PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::TestPHReg::test_summary PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::TestPHReg::test_fit_regularized PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::TestPHReg::test_get_distribution PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::TestPHReg::test_post_estimation PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::TestPHReg::test_predict PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::TestPHReg::test_offset PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::TestPHReg::test_formula PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::TestPHReg::test_formula_cat_interactions PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::TestPHReg::test_fit_regularized_invalid_method_raises PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::TestPHReg::test_summary_after_remove_data PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::TestPHReg::test_predict_formula PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::TestPHReg::test_formula_environment PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::TestPHReg::test_invalid_ties_raises PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_2.csv-efron-True-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_20_1.csv-efron-True-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_100_5.csv-breslow-False-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_1000_10.csv-efron-False-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_100_5.csv-efron-False-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_1.csv-efron-True-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_1000_10.csv-breslow-True-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_100_5.csv-breslow-True-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_20_1.csv-efron-False-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_100_5.csv-breslow-True-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_20_1.csv-breslow-False-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_2.csv-breslow-False-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_20_1.csv-efron-False-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_1000_10.csv-breslow-False-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_20_1.csv-breslow-True-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_1.csv-efron-False-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_100_5.csv-efron-False-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_1000_10.csv-breslow-True-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_2.csv-breslow-False-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_1000_10.csv-efron-False-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_1.csv-efron-False-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_2.csv-efron-True-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_1.csv-breslow-True-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_20_1.csv-breslow-False-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_1.csv-breslow-False-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_1.csv-breslow-False-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_2.csv-breslow-True-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_100_5.csv-efron-True-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_1000_10.csv-breslow-False-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_1000_10.csv-efron-True-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_1.csv-efron-True-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_2.csv-efron-False-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_1000_10.csv-efron-True-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_2.csv-efron-False-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_100_5.csv-breslow-False-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_100_5.csv-efron-True-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_20_1.csv-breslow-True-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_1.csv-breslow-True-False] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_50_2.csv-breslow-True-True] PASSED [ 92%] statsmodels/duration/tests/test_phreg.py::test_r[survival_data_20_1.csv-efron-True-True] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_binomial_loglike_obs[1-0] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_family_link[Poisson-links0] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_tweedie_loglike_obs[1.5] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_binomial_varfunc_deriv PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_family_link_check[Poisson-links0] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_binomial_loglike_obs[1-1] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_family_link[InverseGaussian-links4] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_family_link_check[Gamma-links2] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_invalid_family_link[Tweedie-links6] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_invalid_family_link[InverseGaussian-links4] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_invalid_family_link[NegativeBinomial-links5] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_tweedie_loglike_obs[1.1] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_family_link_check[InverseGaussian-links4] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_invalid_family_link[Binomial-links3] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_family_link[Gaussian-links1] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_family_link_check[Binomial-links3] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_binomial_loglike_obs[0-1] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_family_link[Gamma-links2] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_tweedie_loglike_obs[1.9] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_binomial_loglike_obs[0-0] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_invalid_family_link[Poisson-links0] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_invalid_family_link[Gamma-links2] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_invalid_family_link[Gaussian-links1] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_tweedie_log_wright_bessel PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_family_link[Binomial-links3] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_family_link_check[NegativeBinomial-links5] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_family_link_check[Tweedie-links6] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_family_link_check[Gaussian-links1] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_family_link[NegativeBinomial-links5] PASSED [ 92%] statsmodels/genmod/families/tests/test_family.py::test_family_link[Tweedie-links6] PASSED [ 92%] statsmodels/genmod/tests/test_score_test.py::TestScoreTestGaussian::test_wald_score PASSED [ 92%] statsmodels/genmod/tests/test_score_test.py::TestScoreTestPoissonDispersed::test_wald_score PASSED [ 92%] statsmodels/genmod/tests/test_score_test.py::TestScoreTestPoissonDispersed::test_dispersion PASSED [ 92%] statsmodels/genmod/tests/test_score_test.py::TestScoreTestPoisson::test_dispersion PASSED [ 92%] statsmodels/genmod/tests/test_score_test.py::TestScoreTestPoisson::test_wald_score PASSED [ 92%] statsmodels/genmod/tests/test_score_test.py::TestScoreTestDispersed::test_dispersion PASSED [ 92%] statsmodels/genmod/tests/test_score_test.py::TestScoreTestDispersed::test_wald_score PASSED [ 92%] statsmodels/genmod/tests/test_score_test.py::test_score_test_invalid_hypothesis_raises PASSED [ 92%] statsmodels/genmod/tests/test_score_test.py::TestScoreTest::test_dispersion PASSED [ 92%] statsmodels/genmod/tests/test_score_test.py::TestScoreTest::test_wald_score PASSED [ 92%] statsmodels/multivariate/tests/test_manova.py::test_manova_test_input_validation PASSED [ 92%] statsmodels/multivariate/tests/test_manova.py::test_manova_no_formula PASSED [ 92%] statsmodels/multivariate/tests/test_manova.py::test_manova_sas_example PASSED [ 92%] statsmodels/multivariate/tests/test_manova.py::test_endog_1D_array PASSED [ 92%] statsmodels/multivariate/tests/test_manova.py::test_manova_demeaned PASSED [ 92%] statsmodels/multivariate/tests/test_manova.py::test_manova_no_formula_no_hypothesis PASSED [ 92%] statsmodels/base/tests/test_shrink_pickle.py::TestPickleFormula2::test_remove_data_docstring PASSED [ 92%] statsmodels/base/tests/test_shrink_pickle.py::TestPickleFormula2::test_pickle_wrapper PASSED [ 92%] statsmodels/base/tests/test_shrink_pickle.py::TestPickleFormula2::test_remove_data_pickle PASSED [ 92%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPicklePoissonRegularized::test_remove_data_pickle PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPicklePoissonRegularized::test_remove_data_docstring PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPicklePoissonRegularized::test_pickle_wrapper PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleLogit::test_pickle_wrapper PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleLogit::test_remove_data_docstring PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleLogit::test_remove_data_pickle PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleWLS::test_pickle_wrapper PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleWLS::test_remove_data_pickle PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleWLS::test_remove_data_docstring PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleOLS::test_remove_data_pickle PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleOLS::test_pickle_wrapper PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleOLS::test_remove_data_docstring PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestPickleFormula3::test_remove_data_docstring PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestPickleFormula3::test_remove_data_pickle PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestPickleFormula3::test_pickle_wrapper PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleGLM::test_cached_values_evaluated PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleGLM::test_pickle_wrapper PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleGLM::test_cached_data_removed PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleGLM::test_remove_data_docstring PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleGLM::test_remove_data_pickle PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestPickleFormula5::test_remove_data_pickle PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestPickleFormula5::test_remove_data_docstring PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestPickleFormula5::test_pickle_wrapper PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleRLM::test_remove_data_pickle PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleRLM::test_pickle_wrapper PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleRLM::test_remove_data_docstring PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPicklePoisson::test_pickle_wrapper PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPicklePoisson::test_remove_data_pickle PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPicklePoisson::test_remove_data_docstring PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleNegativeBinomial::test_pickle_wrapper PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleNegativeBinomial::test_remove_data_pickle PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleNegativeBinomial::test_remove_data_docstring PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestPickleFormula4::test_remove_data_pickle PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestPickleFormula4::test_remove_data_docstring PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestPickleFormula4::test_pickle_wrapper PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleGLMConstrained::test_remove_data_pickle PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleGLMConstrained::test_pickle_wrapper PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestRemoveDataPickleGLMConstrained::test_remove_data_docstring PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestPickleFormula::test_remove_data_docstring PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestPickleFormula::test_pickle_wrapper PASSED [ 93%] statsmodels/base/tests/test_shrink_pickle.py::TestPickleFormula::test_remove_data_pickle PASSED [ 93%] statsmodels/tools/tests/test_docstring.py::test_empty_string_ds[\n] PASSED [ 93%] statsmodels/tools/tests/test_docstring.py::test_empty_string_ds[ ] PASSED [ 93%] statsmodels/tools/tests/test_docstring.py::test_remove_parameter PASSED [ 93%] statsmodels/tools/tests/test_docstring.py::test_replace_block PASSED [ 93%] statsmodels/tools/tests/test_docstring.py::test_insert_parameters PASSED [ 93%] statsmodels/tools/tests/test_docstring.py::test_empty_ds PASSED [ 93%] statsmodels/tools/tests/test_docstring.py::test_multiple_sig PASSED [ 93%] statsmodels/tools/tests/test_docstring.py::test_bad PASSED [ 93%] statsmodels/tools/tests/test_docstring.py::test_set_unknown PASSED [ 93%] statsmodels/tools/tests/test_docstring.py::test_empty_string_ds[] PASSED [ 93%] statsmodels/tools/tests/test_docstring.py::test_yield_return PASSED [ 93%] statsmodels/tools/tests/test_docstring.py::test_repeat PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::TestCorrPSD1::test_cov_nearest PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::TestCorrPSD1::test_nearest PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::TestCorrPSD1::test_clipped PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::TestCovPSD::test_cov_nearest PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::test_cov_nearest_min_diag[clipped] PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::test_cov_nearest_min_diag[nearest] PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::test_corr_psd PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::test_corrpsd_threshold[1e-06] PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::test_corrpsd_threshold[1e-15] PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::test_corrpsd_threshold[1e-10] PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::test_corrpsd_threshold[0] PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::Test_Factor::test_cov_nearest_factor_homog_sparse[2] PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::Test_Factor::test_cov_nearest_factor_homog_sparse[1] PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::Test_Factor::test_solve PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::Test_Factor::test_cov_nearest_factor_homog[2] PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::Test_Factor::test_corr_thresholded PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::Test_Factor::test_cov_nearest_factor_homog[1] PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::Test_Factor::test_decorrelate PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::Test_Factor::test_corr_nearest_factor[1] PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::Test_Factor::test_spg_optim PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::Test_Factor::test_corr_nearest_factor_sparse[1] PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::Test_Factor::test_logdet PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::Test_Factor::test_corr_nearest_factor_arrpack PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::Test_Factor::test_corr_nearest_factor[2] PASSED [ 93%] statsmodels/stats/tests/test_corrpsd.py::Test_Factor::test_corr_nearest_factor_sparse[2] PASSED [ 93%] statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog::test_fit_em PASSED [ 93%] statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog::test_llf PASSED [ 93%] statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog::test_bse PASSED [ 93%] statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog::test_summary PASSED [ 93%] statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog::test_fit PASSED [ 93%] statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog::test_predict PASSED [ 93%] statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstShort::test_fit_em PASSED [ 93%] statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstShort::test_fit PASSED [ 93%] statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstShort::test_filter_output PASSED [ 93%] 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statsmodels/regression/tests/test_theil.py::TestTheilLinRestrictionApprox::test_attributes PASSED [ 94%] statsmodels/regression/tests/test_theil.py::TestTheilPanel::test_combine_subset_regression PASSED [ 94%] statsmodels/regression/tests/test_theil.py::TestTheilPanel::test_regression PASSED [ 94%] statsmodels/regression/tests/test_theil.py::TestTheilLinRestriction::test_attributes PASSED [ 94%] statsmodels/regression/tests/test_theil.py::TestTheil3::test_attributes PASSED [ 94%] statsmodels/regression/tests/test_theil.py::TestTheilGLS::test_attributes PASSED [ 94%] statsmodels/stats/tests/test_deltacov.py::TestDeltacovOLS::test_wald_test PASSED [ 94%] statsmodels/stats/tests/test_deltacov.py::TestDeltacovOLS::test_ttest PASSED [ 94%] statsmodels/stats/tests/test_deltacov.py::TestDeltacovOLS::test_diff PASSED [ 94%] statsmodels/stats/tests/test_deltacov.py::TestDeltacovOLS::test_method PASSED [ 94%] statsmodels/stats/tests/test_deltacov.py::test_deltacov_margeff PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEEMultinomialCovType::test_cov_type PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEEMultinomialCovType::test_wrapper PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_weighted PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_equivalence_from_pairs PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_groups PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_invalid_args[False-True] PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_multinomial_input_type[str] PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_nominal_independence PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_margins_gaussian_lists_tuples PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_predict_exposure PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_scoretest PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_compare_logit PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_poisson PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_constraint_covtype PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_compare_poisson PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_invalid_args[True-False] PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_summary_after_remove_data PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_nested_linear PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_stationary_nogrid PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_ordinal_formula PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_invalid_args[True-True] PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_autoregressive PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_compare_score_test[Independence] PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_margins_logistic PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_formulas PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_margins_multinomial PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_multinomial_input_type[int] PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_sensitivity PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_compare_OLS PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_nested_pandas PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_predict_exposure_lists PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_default_time PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_compare_score_test_warnings PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_margins_gaussian PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_equivalence PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_ordinal PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_missing_formula PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_missing PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_margins_poisson PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_poisson_epil PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_formula_environment PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_ordinal_independence PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_ordinal_plot PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_nominal_plot PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_logistic PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_nominal PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_stationary_grid PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_linear_constrained PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_predict PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_invalid_args[False-False] PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_post_estimation PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_offset_formula PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_linear PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEE::test_compare_score_test[Exchangeable] PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEEOrdinalCovType::test_cov_type PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEEOrdinalCovType::test_wrapper PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEEPoissonFormulaCovType::test_cov_type PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_regularized_poisson PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_quasipoisson[True] PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_ar_covsolve PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_grid_ar PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_autoregressive_covariance_matrix_and_summary PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_plots PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_unstructured_incomplete PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_independence_covariance_matrix_and_summary PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_exchangeable_covariance_matrix_and_summary PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_ql_known[Gaussian] PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_quasipoisson[False] PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_qic_warnings PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_global_odds_ratio_summary PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_ex_covsolve PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_ql_known[Poisson] PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_ql_diff[Gaussian] PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_stationary_covsolve PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_regularized_gaussian PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_unstructured_complete PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_unstructured_summary PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_ql_diff[Binomial] PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_gee_results_resid_split PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_stationary_summary PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_missing PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::test_ql_diff[Poisson] PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEEPoissonCovType::test_cov_type PASSED [ 94%] statsmodels/genmod/tests/test_gee.py::TestGEEPoissonCovType::test_wrapper PASSED [ 94%] statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_plot_pandas[int] PASSED [ 94%] statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_plot_both PASSED [ 94%] statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_formatting_errors PASSED [ 94%] statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_plot_rainbow PASSED [ 94%] statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_plot_pandas[str] PASSED [ 94%] statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_recode_series PASSED [ 94%] statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_plottype PASSED [ 94%] statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_formatting PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMBinomialCountConstrainedHC::test_se PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMBinomialCountConstrainedHC::test_params PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMBinomialCountConstrainedHC::test_resid PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMBinomialCountConstrainedHC::test_wald PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMBinomialCountConstrainedHC::test_glm_attr PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMWtdGaussianConstrained::test_params PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMWtdGaussianConstrained::test_se PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMWtdGaussianConstrained::test_resid PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMGaussianOffsetHC::test_resid PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMGaussianOffsetHC::test_se PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMGaussianOffsetHC::test_params PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMGaussianConstrainedHC::test_resid PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMGaussianConstrainedHC::test_params PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMGaussianConstrainedHC::test_se PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMWtdGaussianOffsetHC::test_resid PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMWtdGaussianOffsetHC::test_se PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMWtdGaussianOffsetHC::test_params PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMBinomialCountConstrained::test_se PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMBinomialCountConstrained::test_glm_attr PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMBinomialCountConstrained::test_wald PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMBinomialCountConstrained::test_resid PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMBinomialCountConstrained::test_params PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMGaussianOffset::test_resid PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMGaussianOffset::test_se PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMGaussianOffset::test_params PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMWtdGaussianConstrainedHC::test_resid PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMWtdGaussianConstrainedHC::test_se PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMWtdGaussianConstrainedHC::test_params PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMGaussianConstrained::test_se PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMGaussianConstrained::test_params PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMGaussianConstrained::test_resid PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMWtdGaussianOffset::test_params PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMWtdGaussianOffset::test_se PASSED [ 94%] statsmodels/genmod/tests/test_constrained.py::TestGLMWtdGaussianOffset::test_resid PASSED [ 94%] statsmodels/graphics/tests/test_agreement.py::test_mean_diff_plot PASSED [ 94%] statsmodels/graphics/tests/test_agreement.py::test_mean_diff_plot_linestyles PASSED [ 94%] statsmodels/multivariate/factor_rotation/tests/test_rotation.py::TestAnalyticRotation::test_target_rotation PASSED [ 94%] statsmodels/multivariate/factor_rotation/tests/test_rotation.py::TestAnalyticRotation::test_orthogonal_target PASSED [ 94%] statsmodels/multivariate/factor_rotation/tests/test_rotation.py::test_rotateA_invalid_rotation_method_raises PASSED [ 94%] statsmodels/multivariate/factor_rotation/tests/test_rotation.py::TestWrappers::test_methods PASSED [ 94%] statsmodels/multivariate/factor_rotation/tests/test_rotation.py::TestGPARotation::test_equivalence_orthomax_oblimin PASSED [ 94%] statsmodels/multivariate/factor_rotation/tests/test_rotation.py::TestGPARotation::test_orthogonal_target PASSED [ 94%] statsmodels/multivariate/factor_rotation/tests/test_rotation.py::TestGPARotation::test_orthogonal_partial_target PASSED [ 94%] statsmodels/multivariate/factor_rotation/tests/test_rotation.py::TestGPARotation::test_orthomax PASSED [ 94%] statsmodels/multivariate/factor_rotation/tests/test_rotation.py::TestGPARotation::test_CF PASSED [ 94%] statsmodels/multivariate/factor_rotation/tests/test_rotation.py::TestGPARotation::test_oblimin PASSED [ 94%] statsmodels/imputation/tests/test_ros.py::Test_ROS_MaxCen_GT_MaxUncen::test_cohn PASSED [ 94%] statsmodels/imputation/tests/test_ros.py::Test_ROS_MaxCen_GT_MaxUncen::test_ros_arrays PASSED [ 94%] statsmodels/imputation/tests/test_ros.py::Test_ROS_MaxCen_GT_MaxUncen::test_ros_df PASSED [ 94%] statsmodels/imputation/tests/test_ros.py::Test_ROS_HelselAppendixB::test_cohn PASSED [ 94%] statsmodels/imputation/tests/test_ros.py::Test_ROS_HelselAppendixB::test_ros_df PASSED [ 94%] statsmodels/imputation/tests/test_ros.py::Test_ROS_HelselAppendixB::test_ros_arrays PASSED [ 94%] statsmodels/imputation/tests/test_ros.py::Test_ROS_RNADAdata::test_ros_arrays PASSED [ 94%] statsmodels/imputation/tests/test_ros.py::Test_ROS_RNADAdata::test_ros_df PASSED [ 94%] statsmodels/imputation/tests/test_ros.py::Test_ROS_RNADAdata::test_cohn PASSED [ 94%] statsmodels/imputation/tests/test_ros.py::Test_HalfDLs_80pctNDs::test_ros_arrays PASSED [ 94%] statsmodels/imputation/tests/test_ros.py::Test_HalfDLs_80pctNDs::test_cohn PASSED [ 94%] statsmodels/imputation/tests/test_ros.py::Test_HalfDLs_80pctNDs::test_ros_df PASSED [ 94%] statsmodels/imputation/tests/test_ros.py::Test__ros_plot_pos::test_censored_1 PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test__ros_plot_pos::test_uncensored_2 PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test__ros_plot_pos::test_censored_2 PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test__ros_plot_pos::test_uncensored_1 PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_NoOp_ZeroND::test_ros_df PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_NoOp_ZeroND::test_ros_arrays PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_NoOp_ZeroND::test_cohn PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test__detection_limit_index::test_out_of_bounds PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test__detection_limit_index::test_empty PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test__detection_limit_index::test_populated PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_ROS_OnlyDL_GT_MaxUncen::test_ros_arrays PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_ROS_OnlyDL_GT_MaxUncen::test_ros_df PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_ROS_OnlyDL_GT_MaxUncen::test_cohn PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_cohn_numbers::test_baseline PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_cohn_numbers::test_no_NDs PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_ROS_OneND::test_cohn PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_ROS_OneND::test_ros_df PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_ROS_OneND::test_ros_arrays PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_ROS_HelselArsenic::test_cohn PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_ROS_HelselArsenic::test_ros_arrays PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_ROS_HelselArsenic::test_ros_df PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::test__ros_group_rank PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::test__impute PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::test__norm_plot_pos PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::test__do_ros PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::test_plotting_positions PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test__ros_sort::test_baseline PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test__ros_sort::test_censored_greater_than_max PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_HaflDLs_OneUncensored::test_ros_df PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_HaflDLs_OneUncensored::test_ros_arrays PASSED [ 95%] statsmodels/imputation/tests/test_ros.py::Test_HaflDLs_OneUncensored::test_cohn PASSED [ 95%] statsmodels/nonparametric/tests/test_bandwidths.py::TestGaussian::test_calculate_normal_reference_constant PASSED [ 95%] statsmodels/nonparametric/tests/test_bandwidths.py::TestAllBandwidthZero::test_bandwidth_zero PASSED [ 95%] statsmodels/nonparametric/tests/test_bandwidths.py::TestTriweight::test_calculate_normal_reference_constant PASSED [ 95%] statsmodels/nonparametric/tests/test_bandwidths.py::TestBiweight::test_calculate_normal_reference_constant PASSED [ 95%] statsmodels/nonparametric/tests/test_bandwidths.py::TestBandwidthCalculation::test_calculate_normal_reference_bandwidth PASSED [ 95%] statsmodels/nonparametric/tests/test_bandwidths.py::TestBandwidthCalculation::test_calculate_bandwidth_gaussian PASSED [ 95%] statsmodels/nonparametric/tests/test_bandwidths.py::test_select_sigma_percentile[45] PASSED [ 95%] statsmodels/nonparametric/tests/test_bandwidths.py::test_select_sigma_default_normalization PASSED [ 95%] statsmodels/nonparametric/tests/test_bandwidths.py::test_select_sigma_percentile[40] PASSED [ 95%] statsmodels/nonparametric/tests/test_bandwidths.py::TestAnyBandwidthZero::test_bandwidth_zero PASSED [ 95%] statsmodels/nonparametric/tests/test_bandwidths.py::TestEpanechnikov::test_calculate_normal_reference_constant PASSED [ 95%] statsmodels/stats/tests/test_covariance.py::test_corr_qu_ns_REGRESSION PASSED [ 95%] statsmodels/stats/tests/test_covariance.py::test_transform_corr_normal PASSED [ 95%] statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_scalar PASSED [ 95%] statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_handful_to_tbl PASSED [ 95%] statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_handful_to_ch PASSED [ 95%] statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_vector PASSED [ 95%] statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_all_to_tbl SKIPPED [ 95%] statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_10000_to_ch PASSED [ 95%] statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_invalid_parameters PASSED [ 95%] statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_invalid_parameters PASSED [ 95%] statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_100_random_values PASSED [ 95%] statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_v_less_than_two PASSED [ 95%] statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_scalar PASSED [ 95%] statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_pstrung_boundary PASSED [ 95%] statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_vector PASSED [ 95%] statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_handful_to_known_values PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_slice[True] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_none PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_contiguous PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_1d[True] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_slice[False] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_1d[False] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_dot[False] XFAIL [ 95%] statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_2d[False] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_dot[True] XFAIL [ 95%] statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_right_squeeze_and_pad PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_2d[True] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_3d PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_dtype PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_not_float_like[(1.2+1j)] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_dict_like_strict_mapping PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_optional_dict_like_error PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_string_deprecated_alias_removed_after PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_string PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_wrap_pandas[False] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_right_squeeze PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_wrap_pandas_append PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_array_like_mindim PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_not_int_like[apple] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_bool_like[False] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_optional_dict_like[dict] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_wrap_pandas[True] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_not_int_like[not_integer6] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_not_int_like[(3+2j)] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_int_like[1.0] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_string_deprecated_alias PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_not_int_like[3.2] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_bool_like[True] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_not_float_like[None] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_not_int_like[not_integer1] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_bool_like[1] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_int_like[integer2] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_int_like[2] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_int_like[integer3] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_not_int_like[(2.3+0j)] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_not_float_like[not_floating0] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_bool_like[] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_not_bool_like PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_optional_dict_like[OrderedDict] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_wrap_pandas_append_non_string PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_float_like[(1.2+0j)] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_bool_like[a] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_optional_dict_like[CustomDict] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_optional_dict_like[None] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_not_int_like[(1+0j)] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_not_float_like[3.2] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_float_like[floating3] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_not_float_like[True] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_bool_like[1.2] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_float_like[1.1] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_float_like[floating2] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_float_like[1.0] PASSED [ 95%] statsmodels/tools/validation/tests/test_validation.py::test_optional_string PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_fit_with_box_cox[data-auto] PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_number_of_seasonal_components[data-3-None-1] PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_raise_value_error_when_periods_and_windows_diff_lengths[7-windows1] PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_output_invariant_to_period_order[data-periods_ordered2-None-periods_not_ordered2-None] PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_seasonal_is_datafame_when_input_pandas_and_multiple_periods PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_raise_value_error_when_periods_and_windows_diff_lengths[periods0-1] PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_output_invariant_to_period_order[data-periods_ordered0-windows_ordered0-periods_not_ordered0-windows_not_ordered0] PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_fit_with_box_cox[data--3.0] PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_fit_with_box_cox[data-1] PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_output_similar_to_R_implementation PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_number_of_seasonal_components[data-periods2-None-2] PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_output_invariant_to_period_order[data-periods_ordered1-windows_ordered1-periods_not_ordered1-windows_not_ordered1] PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_number_of_seasonal_components[data-periods1-None-2] PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_plot PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_return_pandas_series_when_input_pandas_and_len_periods_one PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_auto_fit_with_box_cox PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_stl_kwargs_smoke PASSED [ 95%] statsmodels/tsa/stl/tests/test_mstl.py::test_fit_with_box_cox[data-0.1] PASSED [ 95%] statsmodels/stats/tests/test_inference_tools.py::test_mover_confint_invalid_contrast_raises PASSED [ 95%] statsmodels/stats/tests/test_inference_tools.py::test_mover_confint_contrasts PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposureGeneric::test_ttest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposureGeneric::test_waldtest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposureGeneric::test_oth PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposureGeneric::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMLogitOffset::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMLogitOffset::test_margeff SKIPPED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMLogitOffset::test_score_test PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMLogitOffset::test_score_hessian PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Fit::test_ttest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Fit::test_oth PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Fit::test_waldtest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Fit::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Generic::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Generic::test_waldtest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Generic::test_ttest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Generic::test_oth PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMProbit::test_score_test PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMProbit::test_score_hessian PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMProbit::test_margeff SKIPPED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMProbit::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHAC2::test_score_hessian PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHAC2::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHAC2::test_margeff SKIPPED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHAC2::test_score_test PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluGeneric::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluGeneric::test_waldtest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluGeneric::test_oth PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluGeneric::test_ttest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluFit::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluFit::test_waldtest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluFit::test_oth PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluFit::test_ttest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Generic::test_oth PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Generic::test_ttest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Generic::test_waldtest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Generic::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoisson::test_margeff SKIPPED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoisson::test_score_hessian PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoisson::test_score_test PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoisson::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluGeneric::test_ttest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluGeneric::test_waldtest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluGeneric::test_oth PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluGeneric::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluGeneric::test_ttest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluGeneric::test_waldtest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluGeneric::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluGeneric::test_oth PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACPanelGroups::test_score_hessian PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACPanelGroups::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACPanelGroups::test_margeff SKIPPED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACPanelGroups::test_score_test PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluFit::test_oth PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluFit::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluFit::test_waldtest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluFit::test_ttest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACPanel::test_margeff SKIPPED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACPanel::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACPanel::test_score_test PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACPanel::test_score_hessian PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACPanel::test_kwd PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussNonRobust::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussNonRobust::test_score_hessian PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussNonRobust::test_margeff SKIPPED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussNonRobust::test_score_test PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHAC::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHAC::test_score_hessian PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHAC::test_score_test PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHAC::test_margeff SKIPPED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluExposureFit::test_ttest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluExposureFit::test_oth PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluExposureFit::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluExposureFit::test_waldtest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonClu::test_ttest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonClu::test_waldtest PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonClu::test_basic PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonClu::test_oth PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMLogit::test_margeff SKIPPED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMLogit::test_score_test PASSED [ 95%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMLogit::test_score_hessian PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMLogit::test_basic PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonClu::test_ttest PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonClu::test_basic PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonClu::test_waldtest PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonClu::test_oth PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACGroupsum::test_kwd PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACGroupsum::test_score_hessian PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACGroupsum::test_basic PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACGroupsum::test_score_test PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACGroupsum::test_margeff SKIPPED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACUniform2::test_margeff SKIPPED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACUniform2::test_basic PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACUniform2::test_score_hessian PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACUniform2::test_cov_options PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACUniform2::test_score_test PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluExposure::test_basic PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluExposure::test_waldtest PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluExposure::test_oth PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinCluExposure::test_ttest PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussClu::test_basic PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussClu::test_score_hessian PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussClu::test_margeff SKIPPED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussClu::test_score_test PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACUniform::test_score_test PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACUniform::test_margeff SKIPPED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACUniform::test_basic PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACUniform::test_score_hessian PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHACUniform::test_cov_options PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Fit::test_waldtest PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Fit::test_ttest PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Fit::test_basic PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Fit::test_oth PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMProbitOffset::test_score_test PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMProbitOffset::test_margeff SKIPPED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMProbitOffset::test_score_hessian PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMProbitOffset::test_basic PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposure::test_ttest PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposure::test_oth PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposure::test_basic PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposure::test_waldtest PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHC::test_margeff SKIPPED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHC::test_score_hessian PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHC::test_basic PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMGaussHC::test_score_test PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1FitExposure::test_basic PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1FitExposure::test_waldtest PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1FitExposure::test_ttest PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1FitExposure::test_oth PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinClu::test_ttest PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinClu::test_oth PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinClu::test_waldtest PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinClu::test_basic PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluFit::test_basic PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluFit::test_oth PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluFit::test_waldtest PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluFit::test_ttest PASSED [ 96%] statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluFit::test_basic_inference PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Linear::test_other XFAIL [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Linear::test_basic PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Linear::test_summary PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Linear::test_use_t PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Linear::test_hypothesis PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_hypothesis PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_summary PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_other XFAIL [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_use_t PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_bse_other PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_basic PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostep::test_use_t PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostep::test_basic PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostep::test_summary PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostep::test_hypothesis PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostep::test_other PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostepNO::test_use_t PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostepNO::test_basic PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostepNO::test_summary PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostepNO::test_hypothesis PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostepNO::test_other PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_hausman PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_hypothesis PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_input_dimensions PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_other PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_basic PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_summary PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMOLS::test_other XFAIL [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMOLS::test_basic PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO::test_other XFAIL [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO::test_hypothesis PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO::test_basic PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO::test_use_t PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO::test_summary PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_basic PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_use_t PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_other XFAIL [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_summary PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_hypothesis PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_score PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt2::test_basic PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::test_ivgmm1_stata PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::test_ivgmm_summary_after_remove_data PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::test_iv2sls_summary_after_remove_data PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::test_ivgmm0_r PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::test_iv2sls_r PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::test_fittedvalues PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::test_calc_weightmatrix_cov PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::test_calc_weightmatrix_hac_is_symmetric PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::test_calc_weightmatrix_flatkernel_should_be_symmetric XFAIL:].T @ moms_[:-i] / (nobs - i)` for each lag, without adding its transpose. The 'hac' branch (via sandwich_covariance.S_hac_simple) computes the same kind of sum but correctly adds `s + s.T` per lag, which is why the comment in the source says 'can use HAC with flatkernel' -- flatkernel is a stale, broken trial version producing a non-symmetric weight matrix, which is invalid as a GMM weighting matrix.) [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::test_calc_weightmatrix_invalid_method_raises PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::test_noconstant PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::test_gmm_basic PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::test_distquantilesgmm_construction XFAILesults = GMMResults(model=self)` before `self.wargs` is set (wargs is normally only set later, inside fitonce()). GMMResults.__init__ immediately calls self._cov_params(), which does `kwds['wargs'] = self.wargs` and raises AttributeError. This is unconditional -- it happens for any distfn -- and the class's own source already has a '# TODO: something wrong with super' comment at the call site that triggers it.) [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_summary PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_basic PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_hypothesis PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_use_t PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_bse_other PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_other XFAIL [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterOLS_Linear::test_hypothesis PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterOLS_Linear::test_summary PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterOLS_Linear::test_use_t PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterOLS_Linear::test_basic PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterOLS_Linear::test_other XFAIL [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt1::test_basic PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt1::test_use_t PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt1::test_hypothesis PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt1::test_other PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt1::test_summary PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestepNO::test_hypothesis PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestepNO::test_summary PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestepNO::test_other XFAIL [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestepNO::test_basic PASSED [ 96%] statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestepNO::test_use_t PASSED [ 96%] statsmodels/tsa/statespace/tests/test_fixed_params.py::test_structural_validate PASSED [ 96%] statsmodels/tsa/statespace/tests/test_fixed_params.py::test_mle_validate PASSED [ 96%] statsmodels/tsa/statespace/tests/test_fixed_params.py::test_fix_params PASSED [ 96%] statsmodels/tsa/statespace/tests/test_fixed_params.py::test_dynamic_factor_validate PASSED [ 96%] statsmodels/tsa/statespace/tests/test_fixed_params.py::test_score_shape PASSED [ 96%] statsmodels/tsa/statespace/tests/test_fixed_params.py::test_results_extend PASSED [ 96%] statsmodels/tsa/statespace/tests/test_fixed_params.py::test_results_append PASSED [ 96%] statsmodels/tsa/statespace/tests/test_fixed_params.py::test_sarimax_validate PASSED [ 96%] statsmodels/tsa/statespace/tests/test_fixed_params.py::test_results_apply PASSED [ 96%] statsmodels/tsa/statespace/tests/test_fixed_params.py::test_structural PASSED [ 96%] statsmodels/tsa/statespace/tests/test_fixed_params.py::test_nested_fix_params PASSED [ 96%] statsmodels/tsa/statespace/tests/test_fixed_params.py::test_varmax_validate PASSED [ 96%] statsmodels/tsa/statespace/tests/test_fixed_params.py::test_dynamic_factor_diag_error_cov PASSED [ 96%] statsmodels/tsa/statespace/tests/test_fixed_params.py::test_sarimax_nonconsecutive PASSED [ 96%] statsmodels/robust/tests/test_mquantiles.py::TestMQuantiles::test_ols PASSED [ 96%] statsmodels/robust/tests/test_mquantiles.py::TestMQuantiles::test_quantreg PASSED [ 96%] statsmodels/miscmodels/tests/test_generic_mle.py::TestMyParetoRestriction::test_df PASSED [ 96%] statsmodels/miscmodels/tests/test_generic_mle.py::TestMyParetoRestriction::test_ttest PASSED [ 96%] statsmodels/miscmodels/tests/test_generic_mle.py::TestMyParetoRestriction::test_use_t_summary PASSED [ 96%] statsmodels/miscmodels/tests/test_generic_mle.py::TestMyParetoRestriction::test_params PASSED [ 96%] statsmodels/miscmodels/tests/test_generic_mle.py::TestMyParetoRestriction::test_summary PASSED [ 96%] statsmodels/miscmodels/tests/test_generic_mle.py::TestMyPareto1::test_minsupport PASSED [ 96%] statsmodels/miscmodels/tests/test_generic_mle.py::TestMyPareto1::test_params PASSED [ 96%] statsmodels/miscmodels/tests/test_generic_mle.py::TestMyPareto1::test_summary PASSED [ 96%] statsmodels/miscmodels/tests/test_generic_mle.py::TestMyPareto1::test_use_t_summary PASSED [ 96%] statsmodels/miscmodels/tests/test_generic_mle.py::TestMyPareto1::test_ttest PASSED [ 96%] statsmodels/miscmodels/tests/test_generic_mle.py::TestMyPareto1::test_df PASSED [ 96%] statsmodels/miscmodels/tests/test_generic_mle.py::test_summary_after_remove_data PASSED [ 96%] statsmodels/miscmodels/tests/test_generic_mle.py::test_nloglike_matches_nloglikeobs_sum PASSED [ 96%] statsmodels/miscmodels/tests/test_generic_mle.py::test_reduceparams_expandparams_roundtrip PASSED [ 96%] statsmodels/miscmodels/tests/test_generic_mle.py::TestTwoPeakLLHNoExog::test_fit PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_gam_penalty PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_partial_values PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_multivariate_gam_cv PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_cov_params PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_gam_gradient PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_penalized_wls PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_approximation PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_get_sqrt PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_gam_discrete PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_multivariate_penalty PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_make_augmented_matrix PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_multivariate_cubic_splines PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_summary_after_remove_data PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_gam_hessian PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_generic_smoother PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_gam_glm PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_partial_plot PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_train_test_smoothers PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_glm_pirls_compatibility PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_cyclic_cubic_splines PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_multivariate_gam_1d_data PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_partial_values2 PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_multivariate_gam_cv_path PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_zero_penalty PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_spl_s PASSED [ 96%] statsmodels/gam/tests/test_gam.py::test_glmgam_results_hat_matrix_cv_gcv_test_significance PASSED [ 96%] statsmodels/tests/test_x13.py::test_make_var_names PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_defaults[True-True] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_varying[exog-True-False] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_varmax_time_varying[exog-False-True] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_unobserved_components_time_varying[True-False] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_start_end_dates[True] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_varying[trend-False-True] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_invariant[False-False-True] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_varmax_time_varying[trend-True-False] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_defaults[False-False] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_invariant[-2-True-True] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_varmax_time_varying[exog-True-False] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_varmax_time_invariant[True-True] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_unobserved_components_time_varying[False-True] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_varying[exog-False-True] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_invariant[True-True-True] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_varmax_time_varying[trend-False-False] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_invariant[True-False-False] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_start_end_int[range] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_varmax_time_varying[trend-False-True] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_invariant[-2-False-False] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_start_end_int[numpy] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_varying[trend-True-False] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_invariant[False-True-False] PASSED [ 96%] statsmodels/tsa/statespace/tests/test_news.py::test_varmax_time_varying[exog-True-True] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_start_end_dates[False] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_invariant[False-True-True] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_dynamic_factor_time_varying[True-True] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_start_end_int[int64] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_invalid_comparison_type PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_varmax_time_varying[trend-True-True] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_defaults[False-True] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_detailed_revisions[True] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_varying[trend-False-False] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_varmax_time_invariant[False-True] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_dynamic_factor_time_varying[True-False] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_varying[exog-False-False] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_dynamic_factor_time_varying[False-False] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_invariant[-2-False-True] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_invariant[True-True-False] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_grouped_revisions[202] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_news_summary_methods PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_varying[exog-True-True] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_varying[trend-True-True] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_unobserved_components_time_varying[False-False] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_defaults[True-False] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_mixed_revisions[201] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_grouped_revisions[False] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_detailed_revisions[-10] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_comparison_types PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_varmax_time_invariant[True-False] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_dynamic_factor_time_varying[False-True] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_detailed_revisions[200] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_start_end_int[range2] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_invariant[-2-True-False] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_varmax_time_varying[exog-False-False] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_start_end_int[list] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_varmax_time_invariant[False-False] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_invariant[True-False-True] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_invalid PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_sarimax_time_invariant[False-False-False] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_mixed_revisions[-1] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_news.py::test_unobserved_components_time_varying[True-True] PASSED [ 97%] statsmodels/tsa/statespace/tests/test_univariate.py::TestClark1989::test_loglike PASSED [ 97%] statsmodels/tsa/statespace/tests/test_univariate.py::TestClark1989::test_filtered_state PASSED [ 97%] statsmodels/tsa/statespace/tests/test_univariate.py::TestClark1989::test_predicted_state PASSED [ 97%] statsmodels/tsa/statespace/tests/test_univariate.py::TestClark1989::test_smoothed_states PASSED [ 97%] statsmodels/tsa/statespace/tests/test_univariate.py::TestClark1989::test_predicted_state_cov PASSED [ 97%] statsmodels/tsa/statespace/tests/test_univariate.py::TestClark1989::test_smoothed_states_cov PASSED [ 97%] 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statsmodels/stats/tests/test_multivariate_tools.py::test_partial_project_orthogonality PASSED [ 97%] statsmodels/tsa/arima/estimators/tests/test_gls.py::test_brockwell_davis_example_661 PASSED [ 97%] statsmodels/tsa/arima/estimators/tests/test_gls.py::test_results PASSED [ 97%] statsmodels/tsa/arima/estimators/tests/test_gls.py::test_misc PASSED [ 97%] statsmodels/tsa/arima/estimators/tests/test_gls.py::test_arma_kwargs PASSED [ 97%] statsmodels/tsa/arima/estimators/tests/test_gls.py::test_integrated PASSED [ 97%] statsmodels/tsa/arima/estimators/tests/test_gls.py::test_brockwell_davis_example_662 PASSED [ 97%] statsmodels/tsa/arima/estimators/tests/test_gls.py::test_alternate_arma_estimators_valid PASSED [ 97%] statsmodels/tsa/arima/estimators/tests/test_gls.py::test_iterations PASSED [ 97%] statsmodels/tsa/arima/estimators/tests/test_gls.py::test_alternate_arma_estimators_invalid PASSED [ 97%] statsmodels/tsa/arima/estimators/tests/test_gls.py::test_integrated_invalid PASSED [ 97%] statsmodels/genmod/tests/test_qif.py::test_formula[cov_struct1] PASSED [ 97%] statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct0-fam0] PASSED [ 97%] statsmodels/genmod/tests/test_qif.py::test_formula[cov_struct0] PASSED [ 97%] statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct0-fam2] PASSED [ 97%] statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct0-fam1] PASSED [ 97%] statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct0-fam0] PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_formula[cov_struct2] PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct0-fam1] PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct0-fam2] PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_summary_after_remove_data PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct2-fam1] PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct2-fam2] PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct1-fam0] PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct2-fam0] PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_formula_environment PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct1-fam2] PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct1-fam1] PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct1-fam0] PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct2-fam2] PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct2-fam1] PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct1-fam1] PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct1-fam2] PASSED [ 98%] statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct2-fam0] PASSED [ 98%] statsmodels/sandbox/panel/tests/test_random_panel.py::test_short_panel PASSED [ 98%] statsmodels/sandbox/panel/tests/test_random_panel.py::test_panel_sample_rng_default_is_generator PASSED [ 98%] statsmodels/sandbox/panel/tests/test_random_panel.py::test_panel_sample_rng_reproducible PASSED [ 98%] statsmodels/sandbox/panel/tests/test_random_panel.py::test_panel_sample_rng_types PASSED [ 98%] statsmodels/tsa/arima/estimators/tests/test_burg.py::test_brockwell_davis_example_513 PASSED [ 98%] statsmodels/tsa/arima/estimators/tests/test_burg.py::test_itsmr PASSED [ 98%] statsmodels/tsa/arima/estimators/tests/test_burg.py::test_misc PASSED [ 98%] statsmodels/tsa/arima/estimators/tests/test_burg.py::test_brockwell_davis_example_514 PASSED [ 98%] statsmodels/tsa/arima/estimators/tests/test_burg.py::test_invalid PASSED [ 98%] statsmodels/tsa/arima/estimators/tests/test_burg.py::test_nonstationary_series PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_smoothed_state_disturbance_cov PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_scaled_smoothed_estimator_cov PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_forecasts_error PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_smoothed_states_cov PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_smoothed_state_disturbance PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_predicted_states_cov PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_smoothed_forecasts PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_scaled_smoothed_estimator PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_forecasts_error_cov PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_smoothed_measurement_disturbance PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_smoothed_measurement_disturbance_cov PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_forecasts PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_predicted_states PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_smoothed_states PASSED [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_smoothed_state_disturbance_cov SKIPPED_posdef > k_states. However, this test could be used if models of those types were allowed) [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_scaled_smoothed_estimator SKIPPED_posdef > k_states. However, this test could be used if models of those types were allowed) [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_forecasts_error SKIPPED_posdef > k_states. However, this test could be used if models of those types were allowed) [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_forecasts_error_cov SKIPPED_posdef > k_states. However, this test could be used if models of those types were allowed) [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_predicted_states_cov SKIPPED_posdef > k_states. However, this test could be used if models of those types were allowed) [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_smoothed_states_cov SKIPPED_posdef > k_states. However, this test could be used if models of those types were allowed) [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_smoothed_measurement_disturbance SKIPPED_posdef > k_states. However, this test could be used if models of those types were allowed) [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_dimensions SKIPPED_posdef > k_states. However, this test could be used if models of those types were allowed) [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_smoothed_state_disturbance SKIPPED_posdef > k_states. However, this test could be used if models of those types were allowed) [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_forecasts SKIPPED_posdef > k_states. However, this test could be used if models of those types were allowed) [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_predicted_states SKIPPED_posdef > k_states. However, this test could be used if models of those types were allowed) [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_smoothed_states SKIPPED_posdef > k_states. However, this test could be used if models of those types were allowed) [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_loglike SKIPPED_posdef > k_states. However, this test could be used if models of those types were allowed) [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_scaled_smoothed_estimator_cov SKIPPED_posdef > k_states. However, this test could be used if models of those types were allowed) [ 98%] statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_smoothed_measurement_disturbance_cov SKIPPED_posdef > k_states. However, this test could be used if models of those types were allowed) [ 98%] statsmodels/tsa/statespace/tests/test_models.py::test_large_kposdef PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonZi::test_offset_array_like PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonZi::test_df PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonZi::test_exog_names_warning PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonZi::test_summary PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonZi::test_params PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonZi::test_cov_params PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonZi::test_ttest PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonOffset::test_ttest PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonOffset::test_params PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonOffset::test_cov_params PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonOffset::test_summary PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonOffset::test_df PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonMLE::test_df PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonMLE::test_params PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonMLE::test_summary PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonMLE::test_cov_params PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::TestPoissonMLE::test_ttest PASSED [ 98%] statsmodels/miscmodels/tests/test_poisson.py::test_predict_distribution_poisson_mle PASSED [ 98%] statsmodels/regression/tests/test_predict.py::TestWLSPrediction::test_ci PASSED [ 98%] statsmodels/regression/tests/test_predict.py::TestWLSPrediction::test_glm PASSED [ 98%] statsmodels/regression/tests/test_predict.py::test_predict_se PASSED [ 98%] statsmodels/regression/tests/test_predict.py::test_predict_remove_data PASSED [ 98%] statsmodels/regression/tests/test_predict.py::test_prediction_results_mean_conf_int_invalid_method PASSED [ 98%] statsmodels/regression/tests/test_predict.py::test_prediction_results_mean_var_pred_mean PASSED [ 98%] statsmodels/regression/tests/test_predict.py::test_prediction_results_t_test PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::TestBetaIncome::test_influence PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::TestBetaIncome::test_score_test PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::test_hessian_factor_reassembles_hessian PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::test_hessian_observed_argument PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::test_summary_after_remove_data PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::test_llrmixin_set_null_options PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::TestBetaModel::test_methylation_coefficients PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::TestBetaModel::test_methylation_precision PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::TestBetaModel::test_scores PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::TestBetaModel::test_precision_formula PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::TestBetaModel::test_results_other PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::TestBetaModel::test_eval_env PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::TestBetaModel::test_income_coefficients PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::TestBetaModel::test_income_precision PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::TestBetaMeth::test_basic PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::TestBetaMeth::test_resid PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::TestBetaMeth::test_predict_distribution PASSED [ 98%] statsmodels/othermod/tests/test_beta.py::TestBetaMeth::test_oim PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987Double::test_filtered_state PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987Double::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ForecastDoubleComplex::test_filtered_state PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ForecastDoubleComplex::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987Conserve::test_filtered_state PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987Conserve::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ForecastDouble::test_filtered_state PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ForecastDouble::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ConserveAll::test_filtered_state PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ConserveAll::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987Single::test_loglike SKIPPED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987Single::test_filtered_state SKIPPED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989PartialMissing::test_filtered_state PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989PartialMissing::test_predicted_state PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989PartialMissing::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989::test_filtered_state PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989::test_kalman_gain PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ForecastConserve::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ForecastConserve::test_filtered_state PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987DoubleComplex::test_filtered_state PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987DoubleComplex::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_simulate PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_filter PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_representation PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_impulse_responses PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_init_matrices_time_invariant PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_cython PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_slice_notation PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_no_endog PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_initialize_components PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_standardized_forecasts_error PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_missing PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_initialize_components_default_a_is_zero PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_bind PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_initialize_components_pstar_and_r0q0_raises PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_init_matrices_time_varying PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_initialize_components_r0_q0_equivalent_to_pstar PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_initialization PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::test_predict PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ConserveAll::test_filtered_state PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ConserveAll::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ForecastDouble::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ForecastDouble::test_filtered_state PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989Conserve::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989Conserve::test_filtered_state PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ForecastDoubleComplex::test_filtered_state PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ForecastDoubleComplex::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ForecastConserve::test_loglike PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ForecastConserve::test_filtered_state PASSED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987SingleComplex::test_filtered_state SKIPPED [ 98%] statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987SingleComplex::test_loglike SKIPPED [ 98%] statsmodels/stats/tests/test_outliers_influence.py::test_reset_stata PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats2d_nobs::test_basic PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats2d_nobs::test_ttest_2sample PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats2d_nobs::test_confint_mean PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats2d_nobs::test_corr PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats2d_nobs::test_ttest PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats::test_weightstats_ddof_tests PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats::test_comparemeans_convenient_interface PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats::test_comparemeans_convenient_interface_1d PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats::test_weightstats_1 PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats::test_weightstats_3 PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats::test_weightstats_2 PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim2::test_mean PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim2::test_var PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim2::test_sum PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim2::test_quantiles PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim2::test_sem PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim2::test_std PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1n::test_sem PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1n::test_std PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1n::test_sum PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1n::test_mean PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1n::test_quantiles PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1n::test_var PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats2d::test_basic PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats2d::test_corr PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats2d::test_confint_mean PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats2d::test_ttest_2sample PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats2d::test_ttest PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestZTest::test PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats1d_ddof::test_ttest PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats1d_ddof::test_ttest_2sample PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats1d_ddof::test_confint_mean PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats1d_ddof::test_basic PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1::test_sum PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1::test_sem PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1::test_mean PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1::test_std PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1::test_quantiles PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1::test_var PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1t::test_sum PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1t::test_sem PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1t::test_std PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1t::test_mean PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1t::test_var PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestSim1t::test_quantiles PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats2d_ddof::test_ttest_2sample PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats2d_ddof::test_corr PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats2d_ddof::test_basic PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats2d_ddof::test_confint_mean PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::TestWeightstats2d_ddof::test_ttest PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::test_ztest_ztost PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::test_ttest_ind_with_uneq_var PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::test_alternative_deprecated_alias[l-larger] PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::test_ttost_mean_matches_two_one_sided_ttests PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::test_alternative_deprecated_alias[2-sided-two-sided] PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::test_alternative_deprecated_alias[2s-two-sided] PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::test_alternative_invalid PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::test_weightstats_2d_w2 PASSED [ 98%] statsmodels/stats/tests/test_weightstats.py::test_invalid_usevar_raises PASSED [ 99%] statsmodels/stats/tests/test_weightstats.py::test_ztost_ind_matches_two_one_sided_ztests PASSED [ 99%] statsmodels/stats/tests/test_weightstats.py::test_weightstats_len_1 PASSED [ 99%] statsmodels/stats/tests/test_weightstats.py::test_alternative_deprecated_alias[s-smaller] PASSED [ 99%] statsmodels/stats/tests/test_weightstats.py::test_weightstats_2d_w1 PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_no_period PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_defaults_smoke[False] PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_pandas[False] PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_short_class PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_baseline_class PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_squezable_to_1d PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_parameter_checks_period PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_nljump_1_class PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_ntjump_1_class PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_jump_errors PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_defaults_smoke[True] PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_pandas[True] PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_parameter_checks_low_pass PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_pickle PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_nljump_1_ntjump_1_class PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_parameter_checks_seasonal PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_plot PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_parameter_checks_trend PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_default_trend PASSED [ 99%] statsmodels/tsa/stl/tests/test_stl.py::test_period_detection PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_no_enforce PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_dynamic_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_plot_coefficients_of_determination PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_mle PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_params PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_bse_approx PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_loglike PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_results PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_bic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_aic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_dynamic_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_bic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_aic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_no_enforce PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_plot_coefficients_of_determination PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_summary PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_mle PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_bse_approx PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_loglike PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_params PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_results PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_plot_coefficients_of_determination PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_loglike PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_results PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_bic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_aic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_bse_approx PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_mle PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_params PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_dynamic_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_no_enforce PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_dynamic_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_params PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_no_enforce PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_mle PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_plot_coefficients_of_determination PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_bse_approx PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_aic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_bic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_results PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_loglike PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_plot_coefficients_of_determination PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_loglike PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_results PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_bse_approx PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_params PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_mle PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_no_enforce PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_dynamic_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_aic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_bic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_bse_approx PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_mle PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_plot_coefficients_of_determination PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_dynamic_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_params PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_no_enforce PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_bic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_aic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_results PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_loglike PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_summary PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_aic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_bic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_results PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_no_enforce PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_loglike PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_plot_coefficients_of_determination PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_params PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_mle SKIPPEDeve the maximum.) [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_dynamic_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_bse_approx PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_bic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_aic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_params PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_results PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_plot_coefficients_of_determination PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_loglike PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_no_enforce PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_dynamic_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_mle PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_bse_approx PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_results PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_mle PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_loglike PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_summary PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_dynamic_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_bic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_aic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_params PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_plot_coefficients_of_determination PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_bse PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_no_enforce PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_forecast_exog PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_predict_custom_index PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_extend_results PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_summary_after_remove_data PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_recreate_model PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_apply_results PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_misspecification PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_append_results PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_miscellaneous PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_start_params_nans PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_plot_coefficients_of_determination PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_no_enforce PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_loglike PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_results PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_mle PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_params PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_dynamic_predict PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_bse_approx PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_bic PASSED [ 99%] statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_aic PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_testers[sdp-tester3-49] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_testers[equi-tester0-49] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_sim[tester3-3000-200-3.5-equi] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_testers[equi-tester5-50] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_sim[tester1-300-100-3.5-equi] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_testers[equi-tester4-50] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_testers[equi-tester1-49] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_testers[sdp-tester2-49] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_testers[sdp-tester0-49] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_equi PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_testers[equi-tester3-49] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_testers[sdp-tester5-50] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_testers[sdp-tester4-50] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_sdp PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_sim[tester0-300-100-6-sdp] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_testers[equi-tester2-49] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_sim[tester2-300-100-3.5-sdp] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_testers[sdp-tester1-49] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_testers[sdp-tester5-49] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_sim[tester2-300-100-3.5-equi] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_sim[tester0-300-100-6-equi] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_sim[tester1-300-100-3.5-sdp] PASSED [ 99%] statsmodels/stats/tests/test_knockoff.py::test_testers[sdp-tester0-50] PASSED [ 99%] 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"A", "Y": locs = self._annual_to_loc(index) > full_cycle = self._supported[self._period][self._freq_str] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E KeyError: 'ME' statsmodels/tsa/deterministic.py:833: KeyError ________________ test_calendar_seasonality[None-freq_period12] _________________ time_index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') forecast_index = None, freq_period = ('Y', 'M') @pytest.mark.parametrize("freq_period", cs_params) def test_calendar_seasonality(time_index, forecast_index, freq_period): freq, period = freq_period cs = CalendarSeasonality(period, freq) > cs.in_sample(time_index) statsmodels/tsa/tests/test_deterministic.py:166: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ statsmodels/tsa/deterministic.py:851: in in_sample terms = self._get_terms(index) ^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = Seasonal(freq=ME) at 0x7fa76f929040 index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') def _get_terms(self, index: pd.DatetimeIndex | pd.PeriodIndex) -> np.ndarray: if self._period == "D": locs = self._daily_to_loc(index) elif self._period == "W": locs = self._weekly_to_loc(index) elif self._period in ("Q", "QE"): locs = self._quarterly_to_loc(index) else: # "A", "Y": locs = self._annual_to_loc(index) > full_cycle = self._supported[self._period][self._freq_str] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E KeyError: 'ME' statsmodels/tsa/deterministic.py:833: KeyError ________________ test_calendar_seasonality[None-freq_period11] _________________ time_index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') forecast_index = None, freq_period = ('Y', 'Q') @pytest.mark.parametrize("freq_period", cs_params) def test_calendar_seasonality(time_index, forecast_index, freq_period): freq, period = freq_period cs = CalendarSeasonality(period, freq) > cs.in_sample(time_index) statsmodels/tsa/tests/test_deterministic.py:166: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ statsmodels/tsa/deterministic.py:851: in in_sample terms = self._get_terms(index) ^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = Seasonal(freq=QE) at 0x7fa74c17cc50 index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') def _get_terms(self, index: pd.DatetimeIndex | pd.PeriodIndex) -> np.ndarray: if self._period == "D": locs = self._daily_to_loc(index) elif self._period == "W": locs = self._weekly_to_loc(index) elif self._period in ("Q", "QE"): locs = self._quarterly_to_loc(index) else: # "A", "Y": locs = self._annual_to_loc(index) > full_cycle = self._supported[self._period][self._freq_str] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E KeyError: 'QE' statsmodels/tsa/deterministic.py:833: KeyError _________________ test_calendar_seasonality[None-freq_period9] _________________ time_index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') forecast_index = None, freq_period = ('A', 'M') @pytest.mark.parametrize("freq_period", cs_params) def test_calendar_seasonality(time_index, forecast_index, freq_period): freq, period = freq_period cs = CalendarSeasonality(period, freq) > cs.in_sample(time_index) statsmodels/tsa/tests/test_deterministic.py:166: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ statsmodels/tsa/deterministic.py:851: in in_sample terms = self._get_terms(index) ^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = Seasonal(freq=ME) at 0x7fa71cc8b930 index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') def _get_terms(self, index: pd.DatetimeIndex | pd.PeriodIndex) -> np.ndarray: if self._period == "D": locs = self._daily_to_loc(index) elif self._period == "W": locs = self._weekly_to_loc(index) elif self._period in ("Q", "QE"): locs = self._quarterly_to_loc(index) else: # "A", "Y": locs = self._annual_to_loc(index) > full_cycle = self._supported[self._period][self._freq_str] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E KeyError: 'ME' statsmodels/tsa/deterministic.py:833: KeyError ________________ test_calendar_seasonality[False-freq_period9] _________________ time_index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') forecast_index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2001-07-11', '2001-07-12', '2001-07-13'], dtype='datetime64[ns]', length=400, freq='B') freq_period = ('A', 'M') @pytest.mark.parametrize("freq_period", cs_params) def test_calendar_seasonality(time_index, forecast_index, freq_period): freq, period = freq_period cs = CalendarSeasonality(period, freq) > cs.in_sample(time_index) statsmodels/tsa/tests/test_deterministic.py:166: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ statsmodels/tsa/deterministic.py:851: in in_sample terms = self._get_terms(index) ^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = Seasonal(freq=ME) at 0x7fa784bd4520 index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') def _get_terms(self, index: pd.DatetimeIndex | pd.PeriodIndex) -> np.ndarray: if self._period == "D": locs = self._daily_to_loc(index) elif self._period == "W": locs = self._weekly_to_loc(index) elif self._period in ("Q", "QE"): locs = self._quarterly_to_loc(index) else: # "A", "Y": locs = self._annual_to_loc(index) > full_cycle = self._supported[self._period][self._freq_str] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E KeyError: 'ME' statsmodels/tsa/deterministic.py:833: KeyError ________________ test_calendar_seasonality[False-freq_period7] _________________ time_index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') forecast_index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2001-07-11', '2001-07-12', '2001-07-13'], dtype='datetime64[ns]', length=400, freq='B') freq_period = ('Q', 'M') @pytest.mark.parametrize("freq_period", cs_params) def test_calendar_seasonality(time_index, forecast_index, freq_period): freq, period = freq_period cs = CalendarSeasonality(period, freq) > cs.in_sample(time_index) statsmodels/tsa/tests/test_deterministic.py:166: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ statsmodels/tsa/deterministic.py:851: in in_sample terms = self._get_terms(index) ^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = Seasonal(freq=ME) at 0x7fa74c703e30 index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') def _get_terms(self, index: pd.DatetimeIndex | pd.PeriodIndex) -> np.ndarray: if self._period == "D": locs = self._daily_to_loc(index) elif self._period == "W": locs = self._weekly_to_loc(index) elif self._period in ("Q", "QE"): locs = self._quarterly_to_loc(index) else: # "A", "Y": locs = self._annual_to_loc(index) > full_cycle = self._supported[self._period][self._freq_str] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E KeyError: 'ME' statsmodels/tsa/deterministic.py:833: KeyError ________________ test_calendar_seasonality[False-freq_period11] ________________ time_index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') forecast_index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2001-07-11', '2001-07-12', '2001-07-13'], dtype='datetime64[ns]', length=400, freq='B') freq_period = ('Y', 'Q') @pytest.mark.parametrize("freq_period", cs_params) def test_calendar_seasonality(time_index, forecast_index, freq_period): freq, period = freq_period cs = CalendarSeasonality(period, freq) > cs.in_sample(time_index) statsmodels/tsa/tests/test_deterministic.py:166: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ statsmodels/tsa/deterministic.py:851: in in_sample terms = self._get_terms(index) ^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = Seasonal(freq=QE) at 0x7fa74c2cbe90 index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') def _get_terms(self, index: pd.DatetimeIndex | pd.PeriodIndex) -> np.ndarray: if self._period == "D": locs = self._daily_to_loc(index) elif self._period == "W": locs = self._weekly_to_loc(index) elif self._period in ("Q", "QE"): locs = self._quarterly_to_loc(index) else: # "A", "Y": locs = self._annual_to_loc(index) > full_cycle = self._supported[self._period][self._freq_str] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E KeyError: 'QE' statsmodels/tsa/deterministic.py:833: KeyError ________________ test_calendar_seasonality[False-freq_period12] ________________ time_index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') forecast_index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2001-07-11', '2001-07-12', '2001-07-13'], dtype='datetime64[ns]', length=400, freq='B') freq_period = ('Y', 'M') @pytest.mark.parametrize("freq_period", cs_params) def test_calendar_seasonality(time_index, forecast_index, freq_period): freq, period = freq_period cs = CalendarSeasonality(period, freq) > cs.in_sample(time_index) statsmodels/tsa/tests/test_deterministic.py:166: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ statsmodels/tsa/deterministic.py:851: in in_sample terms = self._get_terms(index) ^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = Seasonal(freq=ME) at 0x7fa74c2cbef0 index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') def _get_terms(self, index: pd.DatetimeIndex | pd.PeriodIndex) -> np.ndarray: if self._period == "D": locs = self._daily_to_loc(index) elif self._period == "W": locs = self._weekly_to_loc(index) elif self._period in ("Q", "QE"): locs = self._quarterly_to_loc(index) else: # "A", "Y": locs = self._annual_to_loc(index) > full_cycle = self._supported[self._period][self._freq_str] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E KeyError: 'ME' statsmodels/tsa/deterministic.py:833: KeyError _________________ test_calendar_seasonality[list-freq_period9] _________________ time_index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') forecast_index = [Timestamp('2000-01-03 00:00:00'), Timestamp('2000-01-04 00:00:00'), Timestamp('2000-01-05 00:00:00'), Timestamp('2000-01-06 00:00:00'), Timestamp('2000-01-07 00:00:00'), Timestamp('2000-01-10 00:00:00'), ...] freq_period = ('A', 'M') @pytest.mark.parametrize("freq_period", cs_params) def test_calendar_seasonality(time_index, forecast_index, freq_period): freq, period = freq_period cs = CalendarSeasonality(period, freq) > cs.in_sample(time_index) statsmodels/tsa/tests/test_deterministic.py:166: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ statsmodels/tsa/deterministic.py:851: in in_sample terms = self._get_terms(index) ^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = Seasonal(freq=ME) at 0x7fa75c33e450 index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') def _get_terms(self, index: pd.DatetimeIndex | pd.PeriodIndex) -> np.ndarray: if self._period == "D": locs = self._daily_to_loc(index) elif self._period == "W": locs = self._weekly_to_loc(index) elif self._period in ("Q", "QE"): locs = self._quarterly_to_loc(index) else: # "A", "Y": locs = self._annual_to_loc(index) > full_cycle = self._supported[self._period][self._freq_str] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E KeyError: 'ME' statsmodels/tsa/deterministic.py:833: KeyError ________________ test_calendar_seasonality[list-freq_period12] _________________ time_index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') forecast_index = [Timestamp('2000-01-03 00:00:00'), Timestamp('2000-01-04 00:00:00'), Timestamp('2000-01-05 00:00:00'), Timestamp('2000-01-06 00:00:00'), Timestamp('2000-01-07 00:00:00'), Timestamp('2000-01-10 00:00:00'), ...] freq_period = ('Y', 'M') @pytest.mark.parametrize("freq_period", cs_params) def test_calendar_seasonality(time_index, forecast_index, freq_period): freq, period = freq_period cs = CalendarSeasonality(period, freq) > cs.in_sample(time_index) statsmodels/tsa/tests/test_deterministic.py:166: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ statsmodels/tsa/deterministic.py:851: in in_sample terms = self._get_terms(index) ^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = Seasonal(freq=ME) at 0x7fa75c33c9b0 index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') def _get_terms(self, index: pd.DatetimeIndex | pd.PeriodIndex) -> np.ndarray: if self._period == "D": locs = self._daily_to_loc(index) elif self._period == "W": locs = self._weekly_to_loc(index) elif self._period in ("Q", "QE"): locs = self._quarterly_to_loc(index) else: # "A", "Y": locs = self._annual_to_loc(index) > full_cycle = self._supported[self._period][self._freq_str] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E KeyError: 'ME' statsmodels/tsa/deterministic.py:833: KeyError ________________ test_calendar_seasonality[list-freq_period11] _________________ time_index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') forecast_index = [Timestamp('2000-01-03 00:00:00'), Timestamp('2000-01-04 00:00:00'), Timestamp('2000-01-05 00:00:00'), Timestamp('2000-01-06 00:00:00'), Timestamp('2000-01-07 00:00:00'), Timestamp('2000-01-10 00:00:00'), ...] freq_period = ('Y', 'Q') @pytest.mark.parametrize("freq_period", cs_params) def test_calendar_seasonality(time_index, forecast_index, freq_period): freq, period = freq_period cs = CalendarSeasonality(period, freq) > cs.in_sample(time_index) statsmodels/tsa/tests/test_deterministic.py:166: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ statsmodels/tsa/deterministic.py:851: in in_sample terms = self._get_terms(index) ^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = Seasonal(freq=QE) at 0x7fa74c2cbbf0 index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') def _get_terms(self, index: pd.DatetimeIndex | pd.PeriodIndex) -> np.ndarray: if self._period == "D": locs = self._daily_to_loc(index) elif self._period == "W": locs = self._weekly_to_loc(index) elif self._period in ("Q", "QE"): locs = self._quarterly_to_loc(index) else: # "A", "Y": locs = self._annual_to_loc(index) > full_cycle = self._supported[self._period][self._freq_str] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E KeyError: 'QE' statsmodels/tsa/deterministic.py:833: KeyError _________________ test_calendar_seasonality[list-freq_period7] _________________ time_index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') forecast_index = [Timestamp('2000-01-03 00:00:00'), Timestamp('2000-01-04 00:00:00'), Timestamp('2000-01-05 00:00:00'), Timestamp('2000-01-06 00:00:00'), Timestamp('2000-01-07 00:00:00'), Timestamp('2000-01-10 00:00:00'), ...] freq_period = ('Q', 'M') @pytest.mark.parametrize("freq_period", cs_params) def test_calendar_seasonality(time_index, forecast_index, freq_period): freq, period = freq_period cs = CalendarSeasonality(period, freq) > cs.in_sample(time_index) statsmodels/tsa/tests/test_deterministic.py:166: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ statsmodels/tsa/deterministic.py:851: in in_sample terms = self._get_terms(index) ^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = Seasonal(freq=ME) at 0x7fa71cc7f650 index = DatetimeIndex(['2000-01-03', '2000-01-04', '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-10', '200..., '2003-03-10', '2003-03-11', '2003-03-12'], dtype='datetime64[ns]', length=833, freq='B') def _get_terms(self, index: pd.DatetimeIndex | pd.PeriodIndex) -> np.ndarray: if self._period == "D": locs = self._daily_to_loc(index) elif self._period == "W": locs = self._weekly_to_loc(index) elif self._period in ("Q", "QE"): locs = self._quarterly_to_loc(index) else: # "A", "Y": locs = self._annual_to_loc(index) > full_cycle = self._supported[self._period][self._freq_str] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E KeyError: 'ME' statsmodels/tsa/deterministic.py:833: KeyError _______________________ test_calendar_seasonal_period_a ________________________ def test_calendar_seasonal_period_a(): period = "Y" index = pd.date_range("2000-01-01", freq=MONTH_END, periods=600) cs = CalendarSeasonality(MONTH_END, period=period) > terms = cs.in_sample(index) ^^^^^^^^^^^^^^^^^^^ statsmodels/tsa/tests/test_deterministic.py:460: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ statsmodels/tsa/deterministic.py:851: in in_sample terms = self._get_terms(index) ^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = Seasonal(freq=ME) at 0x7fa71cc7ebd0 index = DatetimeIndex(['2000-01-31', '2000-02-29', '2000-03-31', '2000-04-30', '2000-05-31', '2000-06-30', '200... '2049-10-31', '2049-11-30', '2049-12-31'], dtype='datetime64[ns]', length=600, freq='ME') def _get_terms(self, index: pd.DatetimeIndex | pd.PeriodIndex) -> np.ndarray: if self._period == "D": locs = self._daily_to_loc(index) elif self._period == "W": locs = self._weekly_to_loc(index) elif self._period in ("Q", "QE"): locs = self._quarterly_to_loc(index) else: # "A", "Y": locs = self._annual_to_loc(index) > full_cycle = self._supported[self._period][self._freq_str] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E KeyError: 'ME' statsmodels/tsa/deterministic.py:833: KeyError _______________________ test_calendar_seasonal_period_q ________________________ def test_calendar_seasonal_period_q(): period = "Q" index = pd.date_range("2000-01-01", freq=MONTH_END, periods=600) cs = CalendarSeasonality(MONTH_END, period=period) > terms = cs.in_sample(index) ^^^^^^^^^^^^^^^^^^^ statsmodels/tsa/tests/test_deterministic.py:450: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ statsmodels/tsa/deterministic.py:851: in in_sample terms = self._get_terms(index) ^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = Seasonal(freq=ME) at 0x7fa71cc7d130 index = DatetimeIndex(['2000-01-31', '2000-02-29', '2000-03-31', '2000-04-30', '2000-05-31', '2000-06-30', '200... '2049-10-31', '2049-11-30', '2049-12-31'], dtype='datetime64[ns]', length=600, freq='ME') def _get_terms(self, index: pd.DatetimeIndex | pd.PeriodIndex) -> np.ndarray: if self._period == "D": locs = self._daily_to_loc(index) elif self._period == "W": locs = self._weekly_to_loc(index) elif self._period in ("Q", "QE"): locs = self._quarterly_to_loc(index) else: # "A", "Y": locs = self._annual_to_loc(index) > full_cycle = self._supported[self._period][self._freq_str] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E KeyError: 'ME' statsmodels/tsa/deterministic.py:833: KeyError =============================== warnings summary =============================== ../../../../../../../usr/lib/python3.14/site-packages/_pytest/config/__init__.py:2234 /usr/lib/python3.14/site-packages/_pytest/config/__init__.py:2234: PytestConfigWarning: Failed to import filter module 'statsmodels': error:The test statistic is outside:statsmodels.tools.sm_exceptions.InterpolationWarning: warnings.warn( ../../../../../../../usr/lib/python3.14/site-packages/_pytest/config/__init__.py:2234 /usr/lib/python3.14/site-packages/_pytest/config/__init__.py:2234: PytestConfigWarning: Failed to import filter module 'statsmodels': error:The design matrix is:statsmodels.tools.sm_exceptions.SingularMatrixWarning: warnings.warn( statsmodels/base/tests/test_distributed_estimation.py:357 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/tests/test_distributed_estimation.py:357: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses joblib") statsmodels/base/tests/test_generic_methods.py:110 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/tests/test_generic_methods.py:110: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Model is mutable including using del") statsmodels/base/tests/test_generic_methods.py:522 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/tests/test_generic_methods.py:522: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Modifies the model object in test") statsmodels/base/tests/test_generic_methods.py:550 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/tests/test_generic_methods.py:550: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Modifies the model object in test") statsmodels/base/tests/test_shrink_pickle.py:68 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/tests/test_shrink_pickle.py:68: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/base/tests/test_shrink_pickle.py:112 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/tests/test_shrink_pickle.py:112: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/base/tests/test_shrink_pickle.py:116 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/tests/test_shrink_pickle.py:116: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/datasets/tests/test_utils.py:41 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/datasets/tests/test_utils.py:41: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Disk access") statsmodels/discrete/tests/test_discrete.py:2714 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_discrete.py:2714: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe( statsmodels/discrete/tests/test_discrete.py:2732 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_discrete.py:2732: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe( statsmodels/discrete/tests/test_count_model.py:141 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_count_model.py:141: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="count models are not threadsafe") statsmodels/discrete/tests/test_count_model.py:270 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_count_model.py:270: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="count models are not threadsafe") statsmodels/discrete/tests/test_count_model.py:291 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_count_model.py:291: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="count models are not threadsafe") statsmodels/discrete/tests/test_count_model.py:313 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_count_model.py:313: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="count models are not threadsafe") statsmodels/discrete/tests/test_count_model.py:323 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_count_model.py:323: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="count models are not threadsafe") statsmodels/discrete/tests/test_count_model.py:437 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_count_model.py:437: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="count models are not threadsafe") statsmodels/discrete/tests/test_count_model.py:458 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_count_model.py:458: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="count models are not threadsafe") statsmodels/discrete/tests/test_count_model.py:476 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_count_model.py:476: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="count models are not threadsafe") statsmodels/discrete/tests/test_count_model.py:600 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_count_model.py:600: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="count models are not threadsafe") statsmodels/discrete/tests/test_count_model.py:620 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_count_model.py:620: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="count models are not threadsafe") statsmodels/discrete/tests/test_count_model.py:639 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_count_model.py:639: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="count models are not threadsafe") statsmodels/discrete/tests/test_count_model.py:655 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_count_model.py:655: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="count models are not threadsafe") statsmodels/discrete/tests/test_count_model.py:765 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_count_model.py:765: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="count models are not threadsafe") statsmodels/discrete/tests/test_diagnostic.py:60 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_diagnostic.py:60: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/discrete/tests/test_predict.py:150 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_predict.py:150: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/discrete/tests/test_predict.py:355 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/tests/test_predict.py:355: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/distributions/copula/tests/test_copula.py:915 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/distributions/copula/tests/test_copula.py:915: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/distributions/copula/tests/test_copula.py:929 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/distributions/copula/tests/test_copula.py:929: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/distributions/copula/tests/test_copula.py:950 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/distributions/copula/tests/test_copula.py:950: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/duration/tests/test_survfunc.py:240 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/duration/tests/test_survfunc.py:240: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/emplike/tests/test_aft.py:55 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_aft.py:55: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("Reuses the same emplikeAFT result object") statsmodels/emplike/tests/test_aft.py:61 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_aft.py:61: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("Reuses the same emplikeAFT result object") statsmodels/emplike/tests/test_aft.py:67 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_aft.py:67: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("Reuses the same emplikeAFT result object") statsmodels/emplike/tests/test_descriptive.py:47 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:47: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("calculation sets attributes and is not thread safe") statsmodels/emplike/tests/test_descriptive.py:52 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:52: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("calculation sets attributes and is not thread safe") statsmodels/emplike/tests/test_descriptive.py:58 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:58: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("calculation sets attributes and is not thread safe") statsmodels/emplike/tests/test_descriptive.py:76 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:76: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("calculation sets attributes and is not thread safe") statsmodels/emplike/tests/test_descriptive.py:81 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:81: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("calculation sets attributes and is not thread safe") statsmodels/emplike/tests/test_descriptive.py:97 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:97: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("calculation sets attributes and is not thread safe") statsmodels/emplike/tests/test_descriptive.py:103 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:103: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("calculation sets attributes and is not thread safe") statsmodels/emplike/tests/test_descriptive.py:108 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:108: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("calculation sets attributes and is not thread safe") statsmodels/emplike/tests/test_descriptive.py:119 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:119: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("calculation sets attributes and is not thread safe") statsmodels/emplike/tests/test_descriptive.py:127 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:127: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("calculation sets attributes and is not thread safe") statsmodels/emplike/tests/test_descriptive.py:132 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:132: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("calculation sets attributes and is not thread safe") statsmodels/emplike/tests/test_descriptive.py:142 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:142: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("calculation sets attributes and is not thread safe") statsmodels/emplike/tests/test_descriptive.py:172 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:172: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("calculation sets attributes and is not thread safe") statsmodels/emplike/tests/test_descriptive.py:209 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:209: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("calculation sets attributes and is not thread safe") statsmodels/emplike/tests/test_descriptive.py:226 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:226: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib and monkeypatches Axes.contour") statsmodels/emplike/tests/test_descriptive.py:280 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/emplike/tests/test_descriptive.py:280: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib and monkeypatches Axes.contour") statsmodels/formula/tests/test_formula.py:57 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/formula/tests/test_formula.py:57: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("fit method mutates the model object") statsmodels/formula/tests/test_manager.py:96 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/formula/tests/test_manager.py:96: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("changes global formula_engine variable") statsmodels/formula/tests/test_manager.py:116 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/formula/tests/test_manager.py:116: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="changes global ordering parameter") statsmodels/formula/tests/test_manager.py:131 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/formula/tests/test_manager.py:131: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="changes global ordering parameter") statsmodels/gam/tests/test_gam.py:779 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/gam/tests/test_gam.py:779: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/gam/tests/test_penalized.py:765 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/gam/tests/test_penalized.py:765: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("Some results classes are mutable that affect run") statsmodels/genmod/tests/test_gee.py:205 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/genmod/tests/test_gee.py:205: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/genmod/tests/test_gee.py:1085 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/genmod/tests/test_gee.py:1085: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/genmod/tests/test_gee.py:1829 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/genmod/tests/test_gee.py:1829: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("GEE.dit is not thread safe") statsmodels/genmod/tests/test_gee.py:2057 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/genmod/tests/test_gee.py:2057: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/genmod/tests/test_glm_weights.py:138 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/genmod/tests/test_glm_weights.py:138: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("GLM.fit is not thread safe") statsmodels/graphics/tests/test_agreement.py:8 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_agreement.py:8: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_agreement.py:44 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_agreement.py:44: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_boxplots.py:35 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_boxplots.py:35: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_boxplots.py:54 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_boxplots.py:54: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_boxplots.py:74 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_boxplots.py:74: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_boxplots.py:93 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_boxplots.py:93: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_boxplots.py:115 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_boxplots.py:115: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_boxplots.py:138 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_boxplots.py:138: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_boxplots.py:173 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_boxplots.py:173: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_correlation.py:8 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_correlation.py:8: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_correlation.py:21 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_correlation.py:21: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_dotplot.py:13 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_dotplot.py:13: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_dotplot.py:493 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_dotplot.py:493: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_factorplots.py:23 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_factorplots.py:23: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_factorplots.py:35 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_factorplots.py:35: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_factorplots.py:42 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_factorplots.py:42: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_factorplots.py:56 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_factorplots.py:56: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_factorplots.py:68 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_factorplots.py:68: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_factorplots.py:82 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_factorplots.py:82: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_functional.py:31 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_functional.py:31: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_functional.py:185 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_functional.py:185: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_functional.py:217 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_functional.py:217: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_functional.py:246 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_functional.py:246: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_functional.py:293 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_functional.py:293: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_functional.py:366 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_functional.py:366: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_functional.py:384 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_functional.py:384: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_functional.py:413 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_functional.py:413: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_functional.py:483 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_functional.py:483: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_functional.py:493 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_functional.py:493: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:38 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:38: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:43 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:43: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:48 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:48: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:53 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:53: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:60 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:60: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:70 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:70: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:80 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:80: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:92 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:92: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:102 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:102: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:112 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:112: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:124 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:124: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:135 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:135: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:146 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:146: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:157 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:157: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:169 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:169: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:181 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:181: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:278 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:278: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:285 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:285: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:324 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:324: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:329 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:329: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:341 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:341: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:349 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:349: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:367 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:367: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:437 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:437: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:447 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:447: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:457 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:457: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:468 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:468: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:479 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:479: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:490 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:490: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:495 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:495: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:521 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:521: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:527 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:527: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:536 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:536: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:542 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:542: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:548 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:548: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:554 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:554: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:561 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:561: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:566 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:566: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:571 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:571: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:578 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:578: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:583 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:583: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:588 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:588: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:595 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:595: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:600 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:600: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:605 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:605: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:612 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:612: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:617 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:617: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:642 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:642: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:647 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:647: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:652 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:652: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:657 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:657: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:662 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:662: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:696 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:696: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:727 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:727: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:754 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:754: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_gofplots.py:771 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:771: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_mosaicplot.py:32 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_mosaicplot.py:32: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_mosaicplot.py:82 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_mosaicplot.py:82: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_mosaicplot.py:116 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_mosaicplot.py:116: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_mosaicplot.py:167 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_mosaicplot.py:167: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_mosaicplot.py:219 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_mosaicplot.py:219: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_mosaicplot.py:251 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_mosaicplot.py:251: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_mosaicplot.py:538 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_mosaicplot.py:538: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_mosaicplot.py:552 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_mosaicplot.py:552: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_plot_grids.py:9 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_plot_grids.py:9: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_plot_grids.py:46 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_plot_grids.py:46: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:50 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:50: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:69 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:69: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:85 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:85: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:119 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:119: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:149 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:149: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:172 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:172: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:179 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:179: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:187 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:187: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:194 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:194: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:204 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:204: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:234 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:234: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:251 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:251: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:309 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:309: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:348 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:348: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:385 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:385: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_regressionplots.py:412 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_regressionplots.py:412: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:39 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:39: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:56 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:56: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:73 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:73: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:89 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:89: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:131 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:131: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:163 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:163: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:191 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:191: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:208 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:208: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:233 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:233: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:311 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:311: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:364 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:364: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:392 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:392: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:423 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:423: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:451 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:451: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:459 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:459: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:542 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:542: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:555 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:555: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:565 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:565: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/graphics/tests/test_tsaplots.py:586 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:586: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/imputation/tests/test_mice.py:286 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/imputation/tests/test_mice.py:286: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/imputation/tests/test_mice.py:304 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/imputation/tests/test_mice.py:304: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/imputation/tests/test_mice.py:318 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/imputation/tests/test_mice.py:318: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/imputation/tests/test_mice.py:332 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/imputation/tests/test_mice.py:332: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/multivariate/tests/test_pca.py:49 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/multivariate/tests/test_pca.py:49: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/multivariate/tests/test_pca.py:165 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/multivariate/tests/test_pca.py:165: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Issues and checks warnings") statsmodels/multivariate/tests/test_pca.py:185 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/multivariate/tests/test_pca.py:185: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/nonparametric/tests/test_kernel_regression.py:511 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/nonparametric/tests/test_kernel_regression.py:511: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("Intentionally relies on global random state") statsmodels/regression/tests/test_recursive_ls.py:286 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_recursive_ls.py:286: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="uses matplotlib") statsmodels/regression/tests/test_rolling.py:227 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_rolling.py:227: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="uses matplotlib") statsmodels/stats/tests/test_influence.py:107 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/tests/test_influence.py:107: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/stats/tests/test_meta.py:460 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/tests/test_meta.py:460: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/stats/tests/test_pairwise.py:434 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/tests/test_pairwise.py:434: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/stats/tests/test_pairwise.py:731 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/tests/test_pairwise.py:731: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/stats/tests/test_power.py:107 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/tests/test_power.py:107: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/tools/tests/test_grouputils.py:156 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tools/tests/test_grouputils.py:156: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Modifies self.grouping in-place") statsmodels/tools/tests/test_parallel.py:11 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tools/tests/test_parallel.py:11: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="uses joblib which is not thread safe") statsmodels/compat/patsy.py:13: 22 warnings regression/tests/test_lme.py: 20866 warnings genmod/tests/test_glm.py: 92 warnings regression/tests/test_quantile_regression.py: 180 warnings genmod/tests/test_glm_weights.py: 52 warnings stats/tests/test_anova.py: 518 warnings iolib/tests/test_summary.py: 10 warnings discrete/tests/test_discrete.py: 63 warnings regression/tests/test_regression.py: 82 warnings iolib/tests/test_summary2.py: 56 warnings stats/tests/test_influence.py: 48 warnings imputation/tests/test_bayes_mi.py: 320 warnings regression/tests/test_rolling.py: 48 warnings genmod/tests/test_bayes_mixed_glm.py: 248 warnings stats/tests/test_anova_rm.py: 443 warnings regression/tests/test_recursive_ls.py: 20 warnings robust/tests/test_rlm.py: 10 warnings tools/tests/test_data.py: 18 warnings tsa/ardl/tests/test_ardl.py: 2160 warnings multivariate/tests/test_multivariate_ols.py: 761 warnings formula/tests/test_formula.py: 228 warnings regression/tests/test_processreg.py: 170 warnings base/tests/test_predict.py: 186 warnings miscmodels/tests/test_ordinal_model.py: 287 warnings base/tests/test_data.py: 30 warnings stats/tests/test_diagnostic.py: 16 warnings discrete/tests/test_conditional.py: 155 warnings treatment/tests/test_teffects.py: 19 warnings gam/tests/test_penalized.py: 243 warnings imputation/tests/test_mice.py: 15015 warnings miscmodels/tests/test_tmodel.py: 20 warnings stats/tests/test_mediation.py: 62876 warnings graphics/tests/test_regressionplots.py: 74 warnings regression/tests/test_dimred.py: 22 warnings base/tests/test_generic_methods.py: 480 warnings discrete/tests/test_constrained.py: 149 warnings formula/tests/test_manager.py: 445 warnings genmod/tests/test_gee_glm.py: 128 warnings duration/tests/test_phreg.py: 125 warnings multivariate/tests/test_manova.py: 88 warnings base/tests/test_shrink_pickle.py: 919 warnings genmod/tests/test_gee.py: 612 warnings robust/tests/test_mquantiles.py: 26 warnings gam/tests/test_gam.py: 16 warnings genmod/tests/test_qif.py: 49 warnings othermod/tests/test_beta.py: 373 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/compat/patsy.py:13: DeprecationWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, pd.CategoricalDtype) instead return pd.api.types.is_categorical_dtype(dt) statsmodels/tsa/ardl/tests/test_ardl.py:414 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/ardl/tests/test_ardl.py:414: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/tsa/ardl/tests/test_ardl.py:726 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/ardl/tests/test_ardl.py:726: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/tsa/base/tests/test_tsa_indexes.py:41 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/base/tests/test_tsa_indexes.py:41: FutureWarning: 'Y' is deprecated and will be removed in a future version, please use 'YE' instead. pd.date_range(start="1950-01-01", periods=nobs, freq=YEAR_END), statsmodels/tsa/base/tests/test_tsa_indexes.py:43 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/base/tests/test_tsa_indexes.py:43: FutureWarning: 'Q-DEC' is deprecated and will be removed in a future version, please use 'QE-DEC' instead. pd.date_range(start="1950-01-01", periods=nobs, freq=TWO_QE_DEC), statsmodels/tsa/forecasting/tests/test_stl.py:46 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/forecasting/tests/test_stl.py:46: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/tsa/forecasting/tests/test_theta.py:166 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/forecasting/tests/test_theta.py:166: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/tsa/holtwinters/tests/test_holtwinters.py:815 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/holtwinters/tests/test_holtwinters.py:815: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Issues and checks warnings") statsmodels/tsa/vector_ar/tests/test_var.py:199 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/tests/test_var.py:199: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="uses matplotlib") statsmodels/tsa/vector_ar/tests/test_var.py:212 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/tests/test_var.py:212: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="uses matplotlib") statsmodels/tsa/vector_ar/tests/test_var.py:222 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/tests/test_var.py:222: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="uses matplotlib") statsmodels/tsa/vector_ar/tests/test_var.py:242 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/tests/test_var.py:242: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="uses matplotlib") statsmodels/tsa/vector_ar/tests/test_var.py:468 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/tests/test_var.py:468: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="uses matplotlib") statsmodels/tsa/vector_ar/tests/test_var.py:474 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/tests/test_var.py:474: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="uses matplotlib") statsmodels/tsa/vector_ar/tests/test_var.py:479 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/tests/test_var.py:479: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="uses matplotlib") statsmodels/tsa/vector_ar/tests/test_var.py:484 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/tests/test_var.py:484: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="uses matplotlib") statsmodels/tsa/vector_ar/tests/test_var.py:817 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/tests/test_var.py:817: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="uses matplotlib") statsmodels/tsa/vector_ar/tests/test_var.py:1222 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/tests/test_var.py:1222: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="uses matplotlib") statsmodels/tsa/vector_ar/tests/test_var.py:1247 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/tests/test_var.py:1247: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="uses matplotlib") statsmodels/tsa/statespace/tests/test_dynamic_factor.py:115 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_dynamic_factor.py:115: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:292 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:292: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython code is not thread safe") statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:378 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:378: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython code is not thread safe") statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:461 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:461: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython code is not thread safe") statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:506 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:506: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython code is not thread safe") statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:549 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:549: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython code is not thread safe") statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:560 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:560: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython code is not thread safe") statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:821 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:821: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython code is not thread safe") statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:834 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py:834: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython code is not thread safe") statsmodels/tsa/statespace/tests/test_kalman.py:209 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_kalman.py:209: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("Pickle can't be tested in parallel") statsmodels/tsa/statespace/tests/test_models.py:150 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_models.py:150: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:70 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:70: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:83 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:83: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:91 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:91: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:158 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:158: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:210 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:210: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:229 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:229: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:239 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:239: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:263 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:263: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:270 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:270: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:296 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:296: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:306 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:306: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:330 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:330: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:366 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:366: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:385 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:385: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:395 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:395: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:420 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:420: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:458 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:458: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:480 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:480: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:490 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:490: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:517 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:517: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:540 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:540: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:550 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:550: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:577 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:577: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:608 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:608: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:613 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:613: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:623 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:623: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:649 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:649: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:699 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:699: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:706 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:706: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:717 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:717: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:747 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:747: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:794 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:794: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:825 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:825: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:835 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:835: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:860 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:860: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:897 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:897: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:998 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:998: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:1017 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:1017: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:1055 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:1055: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:1072 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:1072: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:1078 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:1078: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:1125 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:1125: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:1257 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:1257: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:1301 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:1301: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:1309 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:1309: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:1816 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:1816: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:1865 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:1865: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:1921 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:1921: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_sarimax.py:3042 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_sarimax.py:3042: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe("matplotlib is not thread safe") statsmodels/tsa/statespace/tests/test_simulation_smoothing.py:158 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_simulation_smoothing.py:158: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_simulation_smoothing.py:237 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_simulation_smoothing.py:237: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_simulation_smoothing.py:331 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_simulation_smoothing.py:331: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_simulation_smoothing.py:605 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_simulation_smoothing.py:605: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="statespace cython is not thread safe") statsmodels/tsa/statespace/tests/test_varmax.py:38 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_varmax.py:38: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/tsa/statespace/tests/test_varmax.py:56 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_varmax.py:56: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/tsa/statespace/tests/test_varmax.py:200 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_varmax.py:200: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/tsa/statespace/tests/test_varmax.py:205 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_varmax.py:205: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/tsa/statespace/tests/test_varmax.py:258 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_varmax.py:258: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/tsa/statespace/tests/test_varmax.py:263 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_varmax.py:263: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/tsa/statespace/tests/test_varmax.py:437 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_varmax.py:437: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/tsa/statespace/tests/test_varmax.py:442 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_varmax.py:442: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/tsa/statespace/tests/test_varmax.py:493 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_varmax.py:493: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/tsa/statespace/tests/test_varmax.py:499 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_varmax.py:499: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/tsa/statespace/tests/test_varmax.py:512 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_varmax.py:512: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/tsa/statespace/tests/test_varmax.py:619 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_varmax.py:619: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/tsa/statespace/tests/test_varmax.py:644 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_varmax.py:644: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/tsa/statespace/tests/test_varmax.py:650 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_varmax.py:650: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe statsmodels/tsa/stl/tests/test_mstl.py:111 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/stl/tests/test_mstl.py:111: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/tsa/stl/tests/test_stl.py:290 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/stl/tests/test_stl.py:290: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/tsa/tests/test_ar.py:386 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:386: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/tsa/tests/test_ar.py:452 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:452: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/tsa/tests/test_ar.py:1066 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:1066: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/tsa/tests/test_exponential_smoothing.py:643 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_exponential_smoothing.py:643: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Issues and checks warnings") statsmodels/tsa/tests/test_seasonal.py:957 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_seasonal.py:957: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/tsa/tests/test_x13.py:29 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_x13.py:29: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. monthly_data = dta.resample(MONTH_END) ../../../../../../../usr/lib/python3.14/site-packages/pandas/core/resample.py:2359: 1 warning tsa/statespace/tests/test_dynamic_factor_mq.py: 167 warnings tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py: 5 warnings tsa/statespace/tests/test_decompose.py: 2 warnings tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py: 70 warnings tsa/stl/tests/test_stl.py: 1 warning /usr/lib/python3.14/site-packages/pandas/core/resample.py:2359: DeprecationWarning: The 'generic' unit for NumPy timedelta is deprecated, and will raise an error in the future. This includes implicit conversion of bare integers (e.g. `+ 1`). Please use a specific unit instead. + Timedelta(days=1, unit=edges_dti.unit).as_unit(edges_dti.unit) statsmodels/tsa/tests/test_x13.py:86 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_x13.py:86: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") statsmodels/tsa/vector_ar/tests/test_vecm.py:1697 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/tests/test_vecm.py:1697: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") regression/tests/test_lme.py::test_fit_unsupported_kwargs_warns regression/tests/test_lme.py::test_fit_unsupported_kwargs_warns regression/tests/test_lme.py::test_fit_unsupported_kwargs_warns regression/tests/test_lme.py::test_singular regression/tests/test_lme.py::test_fit_unsupported_kwargs_ignored regression/tests/test_lme.py::test_fit_unsupported_kwargs_ignored regression/tests/test_lme.py::test_fit_unsupported_kwargs_ignored /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/mixed_linear_model.py:2384: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals rslt = super().fit( regression/tests/test_lme.py::test_fit_unsupported_kwargs_warns /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_lme.py:1443: ConvergenceWarning: Retrying MixedLM optimization with lbfgs model.fit(cov_type="hc1") regression/tests/test_lme.py::test_fit_unsupported_kwargs_warns /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_lme.py:1443: ConvergenceWarning: Retrying MixedLM optimization with cg model.fit(cov_type="hc1") regression/tests/test_lme.py::test_fit_unsupported_kwargs_warns /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_lme.py:1443: ConvergenceWarning: MixedLM optimization failed, trying a different optimizer may help. model.fit(cov_type="hc1") regression/tests/test_lme.py::test_fit_unsupported_kwargs_warns /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_lme.py:1443: ConvergenceWarning: Gradient optimization failed, |grad| = 1.230293 model.fit(cov_type="hc1") regression/tests/test_lme.py::test_singular /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_lme.py:1334: ConvergenceWarning: Retrying MixedLM optimization with lbfgs mdf = md.fit() regression/tests/test_lme.py::test_singular /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_lme.py:1334: ConvergenceWarning: The MLE may be on the boundary of the parameter space. mdf = md.fit() regression/tests/test_lme.py::test_singular /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_lme.py:1334: ConvergenceWarning: The Hessian matrix at the estimated parameter values is not positive definite. mdf = md.fit() regression/tests/test_lme.py::test_fit_unsupported_kwargs_ignored /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_lme.py:1424: ConvergenceWarning: Retrying MixedLM optimization with lbfgs result = model.fit(cov_type="hc1") regression/tests/test_lme.py::test_fit_unsupported_kwargs_ignored /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_lme.py:1424: ConvergenceWarning: Retrying MixedLM optimization with cg result = model.fit(cov_type="hc1") regression/tests/test_lme.py::test_fit_unsupported_kwargs_ignored /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_lme.py:1424: ConvergenceWarning: MixedLM optimization failed, trying a different optimizer may help. result = model.fit(cov_type="hc1") regression/tests/test_lme.py::test_fit_unsupported_kwargs_ignored /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_lme.py:1424: ConvergenceWarning: Gradient optimization failed, |grad| = 0.822396 result = model.fit(cov_type="hc1") regression/tests/test_lme.py::test_fit_unsupported_kwargs_ignored /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_lme.py:1424: ConvergenceWarning: The MLE may be on the boundary of the parameter space. result = model.fit(cov_type="hc1") regression/tests/test_lme.py::test_fit_unsupported_kwargs_ignored /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_lme.py:1424: ConvergenceWarning: The Hessian matrix at the estimated parameter values is not positive definite. result = model.fit(cov_type="hc1") genmod/tests/test_glm.py::TestRegularized::test_regularized_l1_slsqp_fit_history_iteration /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/genmod/tests/test_glm.py:3029: ConvergenceWarning: Regularized fitting did not converge result = model.fit_regularized( genmod/tests/test_glm.py::TestRegularized::test_regularized_l1_slsqp_fit_history_iteration /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/genmod/tests/test_glm.py:3035: ConvergenceWarning: Regularized fitting did not converge result = model.fit_regularized( genmod/tests/test_glm.py::test_names genmod/tests/test_glm.py::test_names_default genmod/tests/test_gee.py::TestGEE::test_invalid_args[False-True] genmod/tests/test_gee.py::TestGEE::test_invalid_args[True-True] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/genmod/generalized_linear_model.py:319: RuntimeWarning: divide by zero encountered in log exposure = np.log(exposure_array) tsa/statespace/tests/test_mlemodel.py::test_states_index_dateindex /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_mlemodel.py:1346: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. ix = pd.date_range(start="2000", periods=nobs, freq=MONTH_END) tsa/statespace/tests/test_mlemodel.py::test_states_index_dateindex /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_mlemodel.py:1352: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. predicted_ix = pd.date_range(start=ix[0], periods=nobs + 1, freq=MONTH_END) tsa/statespace/tests/test_mlemodel.py::test_integer_params /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/kalman_filter.py:1704: RuntimeWarning: invalid value encountered in scalar divide self.scale = np.sum(scale_obs[d:]) / nobs_k_endog tsa/statespace/tests/test_exact_diffuse_filtering.py: 2 warnings tsa/statespace/tests/test_chandrasekhar.py: 2 warnings tsa/statespace/tests/test_weights.py: 314 warnings tsa/statespace/tests/test_multivariate_switch_univariate.py: 93 warnings tsa/statespace/tests/test_decompose.py: 1 warning tsa/statespace/tests/test_smoothing.py: 164 warnings tsa/statespace/tests/test_univariate.py: 4 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/kalman_smoother.py:443: OutputWarning: The univariate filtering approach diagonalized the observation covariance matrix, so `smoothed_measurement_disturbance_cov` describes the transformed disturbances C_t^{-1} eps_t rather than eps_t. `smoothed_measurement_disturbance` is unaffected. results.update_smoother(smoother) tsa/statespace/tests/test_exact_diffuse_filtering.py::test_irrelevant_state /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/structural.py:1214: ModelWarning: Care should be used when applying a loglikelihood burn to a model with exact diffuse initialization. Some results objects, e.g., degrees of freedom, expect only one of the two to be set. super().__init__(model, params, filter_results, cov_type, **kwargs) stats/tests/test_power.py::test_power_solver_warn /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/power.py:185: RuntimeWarning: invalid value encountered in sqrt pow_ = stats.norm.sf(crit - d * np.sqrt(nobs) / sigma) tsa/holtwinters/tests/test_holtwinters.py::TestHoltWinters::test_holt_damp_r /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/holtwinters/model.py:1700: EstimationWarning: Model has no free parameters to estimate. Set optimized=False to suppress this warning return super().fit( tsa/holtwinters/tests/test_holtwinters.py::test_alternative_minimizers[basinhopping] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/holtwinters/tests/test_holtwinters.py:114: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. index = pd.date_range("2000-1-1", periods=y.shape[0], freq=MONTH_END) tsa/holtwinters/tests/test_holtwinters.py::test_alternative_minimizers[trust-constr] /usr/lib/python3.14/site-packages/scipy/optimize/_differentiable_functions.py:385: UserWarning: delta_grad == 0.0. Check if the approximated function is linear. If the function is linear better results can be obtained by defining the Hessian as zero instead of using quasi-Newton approximations. self.H.update(self.x - self.x_prev, self.g - self.g_prev) tsa/holtwinters/tests/test_holtwinters.py::test_forecast_index_types[date_range] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/holtwinters/tests/test_holtwinters.py:2017: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. index = pd.date_range("2000-1-1", periods=nobs + 36, freq=MONTH_END) tsa/holtwinters/tests/test_holtwinters.py::test_no_params_to_optimize /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/holtwinters/tests/test_holtwinters.py:857: EstimationWarning: Model has no free parameters to estimate. Set optimized=False to suppress this warning mod.fit(smoothing_level=0.5) discrete/tests/test_discrete.py::TestL1AlphaZeroLogit::test_converged /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:438: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals mlefit = super().fit( discrete/tests/test_discrete.py: 2 warnings discrete/tests/test_count_model.py: 3 warnings discrete/tests/test_truncated_model.py: 9 warnings base/tests/test_shrink_pickle.py: 4 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:268: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals mlefit = super().fit( discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_fit_regularized /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/l1_slsqp.py:129: ConvergenceWarning: QC check did not pass for 2 out of 11 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers passed = l1_solvers_common.qc_results( discrete/tests/test_discrete.py: 1 warning discrete/tests/test_count_model.py: 12 warnings discrete/tests/test_truncated_model.py: 2 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/l1_slsqp.py:135: ConvergenceWarning: Could not trim params automatically due to failed QC check. Trimming using trim_mode == 'size' will still work. params, trimmed = l1_solvers_common.do_trim_params( discrete/tests/test_discrete.py::TestL1AlphaZeroMNLogit::test_basic_results discrete/tests/test_discrete.py::test_mnlogit_basinhopping discrete/tests/test_discrete.py::test_mnlogit_float_name discrete/tests/test_discrete.py::TestMNLogitL1Compatability::test_params /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:858: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals mnfit = base.LikelihoodModel.fit( discrete/tests/test_discrete.py: 28 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/optimizer.py:536: PerfectSeparationWarning: Perfect separation or prediction detected, parameter may not be identified callback(newparams) discrete/tests/test_discrete.py::TestPoissonL1Compatability::test_bad_r_matrix /usr/lib/python3.14/site-packages/numpy/_core/fromnumeric.py:83: RuntimeWarning: overflow encountered in reduce return ufunc.reduce(obj, axis, dtype, out, **passkwargs) tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[MS-Q-JAN] tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[M-Q-JAN] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py:1589: FutureWarning: 'Q-JAN' is deprecated and will be removed in a future version, please use 'QE-JAN' instead. dates_Q = pd.date_range(start="2000", periods=nobs_Q, freq=freq_Q) tsa/statespace/tests/test_dynamic_factor_mq.py: 77 warnings tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py: 2 warnings tsa/statespace/tests/test_decompose.py: 1 warning tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py: 34 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/dynamic_factor_mq.py:1576: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. quarterly_resamp = quarterly_resamp.resample(QUARTER_END).first() tsa/statespace/tests/test_dynamic_factor_mq.py: 77 warnings tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py: 2 warnings tsa/statespace/tests/test_decompose.py: 1 warning tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py: 34 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/dynamic_factor_mq.py:1577: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. quarterly_resamp = quarterly_resamp.resample(MONTH_END).first() tsa/statespace/tests/test_dynamic_factor_mq.py::test_standardized_MQ[False] tsa/statespace/tests/test_dynamic_factor_mq.py::test_news_MQ tsa/statespace/tests/test_dynamic_factor_mq.py::test_standardized_MQ[True] tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_k_factor1_factor_order_6 /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py:318: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. log_levels_Q = log_levels_Q.resample(QUARTER_END).sum().iloc[:-1] * 100 tsa/statespace/tests/test_dynamic_factor_mq.py: 10 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py:434: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. log_levels_Q = log_levels_Q.resample(QUARTER_END).sum().iloc[:-1] * 100 tsa/statespace/tests/test_dynamic_factor_mq.py::test_invalid_model_specification /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py:1445: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. dta, index=pd.date_range(start="2000", periods=10, freq=MONTH_END) tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[M-QS] tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[M-QS-DEC] tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[M-Q-DEC] tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[M-Q] tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[M-Q-JAN] tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[M-QS-APR] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py:1581: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. dates_M = pd.date_range(start="2000", periods=nobs_M, freq=freq_M) tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[MS-Q-DEC] tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[M-Q-DEC] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py:1589: FutureWarning: 'Q-DEC' is deprecated and will be removed in a future version, please use 'QE-DEC' instead. dates_Q = pd.date_range(start="2000", periods=nobs_Q, freq=freq_Q) tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[MS-Q] tsa/statespace/tests/test_dynamic_factor_mq.py::test_date_indexes[M-Q] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py:1589: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. dates_Q = pd.date_range(start="2000", periods=nobs_Q, freq=freq_Q) tsa/statespace/tests/test_dynamic_factor_mq.py::test_filter_reproduces_model_loglike /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/dynamic_factor_mq.py:2436: ConvergenceWarning: EM reached maximum number of iterations (5), without achieving convergence: llf=-187.98, convergence criterion=0.0042566 (while specified tolerance was 1e-06) return self.fit_em( discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_fit_regularized discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_fit_regularized discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_fit_regularized discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_fit_regularized /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/l1_slsqp.py:129: ConvergenceWarning: QC check did not pass for 4 out of 4 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers passed = l1_solvers_common.qc_results( discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_fit_regularized discrete/tests/test_truncated_model.py::TestRegularizedHurdleSimulated::test_predict /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/l1_slsqp.py:129: ConvergenceWarning: QC check did not pass for 2 out of 6 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers passed = l1_solvers_common.qc_results( discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_fit_regularized /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/l1_slsqp.py:129: ConvergenceWarning: QC check did not pass for 1 out of 5 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers passed = l1_solvers_common.qc_results( discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_fit_regularized /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/l1_slsqp.py:129: ConvergenceWarning: QC check did not pass for 3 out of 7 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers passed = l1_solvers_common.qc_results( discrete/tests/test_count_model.py: 5 warnings discrete/tests/test_truncated_model.py: 10 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:268: HessianInversionWarning: Inverting hessian failed, no bse or cov_params available mlefit = super().fit( discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_fit_regularized /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/l1_slsqp.py:129: ConvergenceWarning: QC check did not pass for 1 out of 3 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers passed = l1_solvers_common.qc_results( discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_fit_regularized /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/l1_slsqp.py:129: ConvergenceWarning: QC check did not pass for 2 out of 5 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers passed = l1_solvers_common.qc_results( discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_fit_regularized discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_fit_regularized discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_fit_regularized /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/l1_slsqp.py:129: ConvergenceWarning: QC check did not pass for 3 out of 6 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers passed = l1_solvers_common.qc_results( nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_continuousdata_lc_cvls /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/nonparametric/kernel_regression.py:313: RuntimeWarning: invalid value encountered in divide B_x = (G_numer * d_fx - G_denom * d_mx) / (G_denom**2) stats/tests/test_tost.py::test_tost_asym /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/weightstats.py:1526: RuntimeWarning: invalid value encountered in log low = transform(low) graphics/tests/test_gofplots.py::test_qqplot_unequal /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:383: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") graphics/tests/test_gofplots.py::test_qqplot_unequal /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:388: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") graphics/tests/test_gofplots.py::test_qqplot_unequal /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_gofplots.py:396: PytestUnknownMarkWarning: Unknown pytest.mark.thread_unsafe - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @pytest.mark.thread_unsafe(reason="Uses matplotlib") tools/tests/test_eval_measures.py: 12 warnings /usr/lib/python3.14/site-packages/numpy/_core/fromnumeric.py:3862: RuntimeWarning: Mean of empty slice return _methods._mean(a, axis=axis, dtype=dtype, tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[bias] tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[medianabs] tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[mse] tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[rmse] tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[medianbias] tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[meanabs] /usr/lib/python3.14/site-packages/numpy/_core/_methods.py:134: RuntimeWarning: invalid value encountered in divide ret = um.true_divide( tools/tests/test_eval_measures.py::test_measures_empty_input[bias] tools/tests/test_eval_measures.py::test_measures_empty_input[meanabs] tools/tests/test_eval_measures.py::test_measures_empty_input[medianbias] tools/tests/test_eval_measures.py::test_measures_empty_input[rmse] tools/tests/test_eval_measures.py::test_measures_empty_input[medianabs] tools/tests/test_eval_measures.py::test_measures_empty_input[mse] /usr/lib/python3.14/site-packages/numpy/_core/_methods.py:142: RuntimeWarning: invalid value encountered in scalar divide ret = ret.dtype.type(ret / rcount) tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[vare] tools/tests/test_eval_measures.py::test_measures_empty_input[vare] tsa/statespace/tests/test_sarimax.py::test_plot_too_few_obs /usr/lib/python3.14/site-packages/numpy/_core/fromnumeric.py:4270: RuntimeWarning: Degrees of freedom <= 0 for slice return _methods._var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[vare] tools/tests/test_eval_measures.py::test_measures_empty_input[vare] tsa/statespace/tests/test_sarimax.py::test_plot_too_few_obs /usr/lib/python3.14/site-packages/numpy/_core/_methods.py:178: RuntimeWarning: invalid value encountered in divide arrmean = um.true_divide(arrmean, div, out=arrmean, tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[vare] /usr/lib/python3.14/site-packages/numpy/_core/_methods.py:208: RuntimeWarning: invalid value encountered in divide ret = um.true_divide( tools/tests/test_eval_measures.py::test_measures_empty_input[vare] tsa/statespace/tests/test_sarimax.py::test_plot_too_few_obs /usr/lib/python3.14/site-packages/numpy/_core/_methods.py:211: RuntimeWarning: invalid value encountered in scalar divide ret = ret.dtype.type(ret / rcount) tools/tests/test_eval_measures.py::test_measures_empty_input[rmspe] tools/tests/test_eval_measures.py::test_measures_empty_input_keeps_axis_shape[rmspe] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tools/eval_measures.py:131: RuntimeWarning: Mean of empty slice mspe = np.nanmean(percentage_error ** 2, axis=axis) * 100 tsa/tests/test_seasonal.py::TestDecompose::test_2d /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_seasonal.py:260: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. index = pd.date_range(start="1/1/1951", periods=len(data), freq=QUARTER_END) tsa/tests/test_seasonal.py::TestDecompose::test_pandas /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_seasonal.py:387: FutureWarning: 'Y' is deprecated and will be removed in a future version, please use 'YE' instead. freq_override_data.index = pd.date_range( tsa/tests/test_seasonal.py::test_seasonal_decompose_smoke /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_seasonal.py:907: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. x, pd.date_range(start="1/1/1951", periods=len(x), freq=QUARTER_END) tsa/tests/test_seasonal.py::test_seasonal_decompose_too_short /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_seasonal.py:849: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. dates = pd.date_range("2000-01-31", periods=4, freq=QUARTER_END) tsa/tests/test_seasonal.py::test_seasonal_decompose_too_short /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_seasonal.py:856: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. dates = pd.date_range("2000-01-31", periods=12, freq=MONTH_END) tsa/tests/test_stattools.py::TestLeybourneMcCabe::test_dbaa_results tsa/statespace/tests/test_sarimax.py::test_sarimax_starting_values_few_obsevations_long_ma tsa/forecasting/tests/test_stl.py::test_get_prediction tsa/statespace/tests/test_impulse_responses.py::test_varmax tsa/statespace/tests/test_impulse_responses.py::test_varmax tsa/statespace/tests/test_fixed_params.py::test_varmax_validate /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/mlemodel.py:737: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals mlefit = super().fit( tsa/tests/test_stattools.py::test_acovf2d /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_stattools.py:1829: FutureWarning: 'Y' is deprecated and will be removed in a future version, please use 'YE' instead. dta.index = date_range(start="1700", end="2009", freq=YEAR_END)[:309] tsa/tests/test_stattools.py::test_arma_order_select_ic tsa/tests/test_stattools.py::test_arma_order_select_ic tsa/tests/test_stattools.py::test_arma_order_select_ic tsa/statespace/tests/test_sarimax.py::test_sarimax_starting_values_few_obsevations_long_ma /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/mlemodel.py:679: EstimationWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters. start_params = self.start_params tsa/tests/test_stattools.py::test_arma_order_select_ic /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_stattools.py:1980: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. index = pd.date_range("2000-1-1", freq=MONTH_END, periods=len(y)) tsa/tests/test_stattools.py::test_pacf_1_obs /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/linear_model.py:1675: RuntimeWarning: invalid value encountered in scalar divide r[k] = (x[0:-k] * x[k:]).sum() / (n - k * adj_needed) tsa/tests/test_stattools.py::test_pacf_1_obs /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/stattools/_stattools.py:1111: SingularMatrixWarning: Matrix is singular. Using pinv. yule_walker(x, k, method=method, result_object=False)[0][-1] tsa/tests/test_stattools.py::test_acovf_all_missing /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/stattools/_stattools.py:560: RuntimeWarning: invalid value encountered in scalar divide xo = x - x.sum() / notmask_int.sum() tsa/tests/test_stattools.py::test_acovf_all_missing /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/stattools/_stattools.py:612: RuntimeWarning: invalid value encountered in divide acov = np.fft.ifft(Frf * np.conjugate(Frf))[:nobs] / d[nobs - 1 :] tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_2d_input_with_missing_values /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_stattools.py:1118: UserWarning: Early subset of data for variable 2 has too few non-missing observations to calculate test statistic. _result = breakvar_heteroskedasticity_test(input_residuals) tsa/tests/test_stattools.py::TestRUR::test_pval /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_stattools.py:1792: InterpolationWarning: The test statistic is outside of the range of p-values available in the look-up table. The actual p-value is smaller than the p-value returned. _, simple_pval, _ = self.simple_rur(self.x) tsa/tests/test_stattools.py::TestRUR::test_teststat /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_stattools.py:1786: InterpolationWarning: The test statistic is outside of the range of p-values available in the look-up table. The actual p-value is smaller than the p-value returned. simple_rur_stat, _, _ = self.simple_rur(self.x) tsa/tests/test_tsa_tools.py::test_freq_to_period[freq_expected2] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tsatools.py:980: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. freq = to_offset(freq) # go ahead and standardize tsa/tests/test_tsa_tools.py::test_freq_to_period[freq_expected2] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_tsa_tools.py:608: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. assert_equal(tools.freq_to_period(to_offset(freq)), expected) tsa/tests/test_tsa_tools.py::test_freq_to_period[freq_expected0] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tsatools.py:980: FutureWarning: 'Y' is deprecated and will be removed in a future version, please use 'YE' instead. freq = to_offset(freq) # go ahead and standardize tsa/tests/test_tsa_tools.py::test_freq_to_period[freq_expected0] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_tsa_tools.py:608: FutureWarning: 'Y' is deprecated and will be removed in a future version, please use 'YE' instead. assert_equal(tools.freq_to_period(to_offset(freq)), expected) tsa/tests/test_tsa_tools.py::test_freq_to_period[freq_expected1] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tsatools.py:980: FutureWarning: 'A-MAR' is deprecated and will be removed in a future version, please use 'YE-MAR' instead. freq = to_offset(freq) # go ahead and standardize tsa/tests/test_tsa_tools.py::test_freq_to_period[freq_expected1] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_tsa_tools.py:608: FutureWarning: 'A-MAR' is deprecated and will be removed in a future version, please use 'YE-MAR' instead. assert_equal(tools.freq_to_period(to_offset(freq)), expected) tsa/vector_ar/tests/test_svar.py: 46 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/svar_model.py:459: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals super() tsa/filters/tests/test_hamilton_filter.py::test_minimum_length_works[2-3] tsa/filters/tests/test_hamilton_filter.py::test_minimum_length_works[11-7] tsa/filters/tests/test_hamilton_filter.py::test_minimum_length_works[7-3] tsa/filters/tests/test_hamilton_filter.py::test_minimum_length_works[11-3] tsa/filters/tests/test_hamilton_filter.py::test_minimum_length_works[7-7] tsa/filters/tests/test_hamilton_filter.py::test_minimum_length_works[2-7] tsa/filters/tests/test_hamilton_filter.py::test_minimum_length_works[5-3] tsa/filters/tests/test_hamilton_filter.py::test_minimum_length_works[5-7] tsa/tests/test_ar.py::test_no_obs_for_adjustment /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/linear_model.py:1954: RuntimeWarning: divide by zero encountered in scalar divide return np.dot(wresid, wresid) / self.df_resid tsa/base/tests/test_tsa_indexes.py::test_prediction_increment_unsupported tsa/base/tests/test_tsa_indexes.py::test_instantiation_valid tsa/base/tests/test_tsa_indexes.py::test_instantiation_valid tsa/base/tests/test_tsa_indexes.py::test_instantiation_valid tsa/base/tests/test_tsa_indexes.py::test_instantiation_valid tsa/statespace/tests/test_sarimax.py::test_simple_differencing_strindex tsa/statespace/tests/test_sarimax.py::test_simple_differencing_strindex /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/base/tsa_model.py:566: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format. _index = to_datetime(index) tsa/base/tests/test_tsa_indexes.py::test_prediction_increment_unsupported /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/base/tsa_model.py:480: ValueWarning: An unsupported index was provided. As a result, forecasts cannot be generated. To use the model for forecasting, use on the supported classes of index. self._init_dates(dates, freq) tsa/statespace/tests/test_multivariate_switch_univariate.py: 60 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py:171: OutputWarning: The univariate filtering approach diagonalized the observation covariance matrix, so `smoothed_measurement_disturbance_cov` describes the transformed disturbances C_t^{-1} eps_t rather than eps_t. `smoothed_measurement_disturbance` is unaffected. res_switch.update_smoother(smoother) tsa/filters/tests/test_filters.py::TestFilters::test_pandas2d /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/filters/tests/test_filters.py:957: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. data, date_range(start="1/1/1951", periods=len(data), freq=QUARTER_END) tsa/filters/tests/test_filters.py::TestFilters::test_pandas2d /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/filters/tests/test_filters.py:961: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. data, date_range(start="1/1/1951", periods=len(data), freq=QUARTER_END) tsa/filters/tests/test_filters.py::test_hpfilter_pandas /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/filters/tests/test_filters.py:908: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. index = date_range(start="1959-01-01", end="2009-10-01", freq=QUARTER_END) tsa/filters/tests/test_filters.py::test_bking_pandas /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/filters/tests/test_filters.py:867: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. index = date_range(start="1959-01-01", end="2009-10-01", freq=QUARTER_END) tsa/filters/tests/test_filters.py::test_cfitz_pandas /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/filters/tests/test_filters.py:888: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. index = date_range(start="1959-01-01", end="2009-10-01", freq=QUARTER_END) tsa/statespace/tests/test_structural.py::test_fixed_slope_warn tsa/statespace/tests/test_structural.py::test_fixed_slope_warn tsa/statespace/tests/test_structural.py::test_fixed_slope tsa/statespace/tests/test_structural.py::test_fixed_slope tsa/statespace/tests/test_structural.py::test_fixed_intercept tsa/statespace/tests/test_structural.py::test_fixed_intercept /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_structural.py:55: SpecificationWarning: Specified model does not contain a stochastic element; irregular component added. mod = UnobservedComponents(values["unemp"], **kwargs) tsa/tests/test_deterministic.py::test_seasonality_smoke[datetime-None] tsa/tests/test_deterministic.py::test_fourier_smoke[period-None] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_deterministic.py:36: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. idx = pd.date_range("2000-01-01", periods=137, freq=MONTH_END) tsa/tests/test_deterministic.py: 12 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/deterministic.py:561: FutureWarning: 'H' is deprecated and will be removed in a future version, please use 'h' instead. index = pd.date_range("2020-01-01", freq=freq, periods=1) tsa/tests/test_deterministic.py::test_calendar_time_trend_smoke[None] tsa/tests/test_deterministic.py::test_calendar_fourier_smoke[None] tsa/tests/test_deterministic.py::test_calendar_fourier_smoke[False] tsa/tests/test_deterministic.py::test_calendar_time_trend_smoke[False] tsa/tests/test_deterministic.py::test_calendar_time_trend_smoke[list] tsa/tests/test_deterministic.py::test_calendar_fourier_smoke[list] tsa/tests/test_deterministic.py::test_check_index_type tsa/tests/test_deterministic.py::test_forbidden_index /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/deterministic.py:561: FutureWarning: 'Y' is deprecated and will be removed in a future version, please use 'YE' instead. index = pd.date_range("2020-01-01", freq=freq, periods=1) tsa/tests/test_deterministic.py: 12 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/deterministic.py:561: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. index = pd.date_range("2020-01-01", freq=freq, periods=1) tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period11] tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period11] tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period11] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/deterministic.py:561: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. index = pd.date_range("2020-01-01", freq=freq, periods=1) tsa/tests/test_deterministic.py::test_range_index_basic /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_deterministic.py:549: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. idx = pd.date_range("2000-1-1", freq=MONTH_END, periods=120) tsa/tests/test_deterministic.py::test_calendar_seasonal_period_a /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_deterministic.py:458: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. index = pd.date_range("2000-01-01", freq=MONTH_END, periods=600) tsa/tests/test_deterministic.py::test_calendar_seasonal_period_q /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_deterministic.py:448: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. index = pd.date_range("2000-01-01", freq=MONTH_END, periods=600) discrete/tests/test_conditional.py::test_logit_formula discrete/tests/test_conditional.py::test_logit_formula /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/conditional_models.py:303: ModelWarning: Dropped 1 groups and 50 observations for having no within-group variance super().__init__(endog, exog, missing=missing, **kwargs) discrete/tests/test_conditional.py::test_logit_formula discrete/tests/test_conditional.py::test_logit_formula discrete/tests/test_conditional.py::test_logit_formula discrete/tests/test_conditional.py::test_logit_formula /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/conditional_models.py:377: RuntimeWarning: overflow encountered in scalar multiply v = f(t - 1, k) + f(t - 1, k - 1) * exb[t - 1] discrete/tests/test_conditional.py::test_logit_formula discrete/tests/test_conditional.py::test_logit_formula /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/conditional_models.py:411: RuntimeWarning: overflow encountered in scalar multiply d = c * h * ex[t - 1, :] discrete/tests/test_conditional.py::test_logit_formula discrete/tests/test_conditional.py::test_logit_formula /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/conditional_models.py:413: RuntimeWarning: overflow encountered in scalar multiply u, v = a + c * h, b + d + e * h discrete/tests/test_conditional.py::test_logit_formula discrete/tests/test_conditional.py::test_logit_formula discrete/tests/test_conditional.py::test_logit_formula discrete/tests/test_conditional.py::test_logit_formula /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/conditional_models.py:413: RuntimeWarning: overflow encountered in multiply u, v = a + c * h, b + d + e * h discrete/tests/test_conditional.py::test_logit_formula discrete/tests/test_conditional.py::test_logit_formula /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/conditional_models.py:442: RuntimeWarning: invalid value encountered in divide return self._xy[grp] - h / d discrete/tests/test_conditional.py::test_logit_formula discrete/tests/test_conditional.py::test_logit_formula /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/conditional_models.py:181: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals rslt = super().fit( tsa/vector_ar/tests/test_coint.py::TestCointJoh12::test_basic tsa/vector_ar/tests/test_coint.py::TestCointJohMin18::test_normalization tsa/vector_ar/tests/test_coint.py::test_coint_johansen_0lag tsa/vector_ar/tests/test_coint.py::test_johansen_result_aliases_and_rkt_meth tsa/vector_ar/tests/test_coint.py::TestCointJoh09::test_table_trace tsa/vector_ar/tests/test_coint.py::TestCointJoh25::test_table_trace tsa/vector_ar/tests/test_vecm.py::test_select_coint_rank tsa/vector_ar/tests/test_vecm.py::test_coint_rank_results_summary /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/vecm.py:717: ComplexWarning: Casting complex values to real discards the imaginary part lr1[i] = -t * np.sum(tmp, 0) tsa/vector_ar/tests/test_coint.py::TestCointJoh12::test_basic tsa/vector_ar/tests/test_coint.py::TestCointJohMin18::test_normalization tsa/vector_ar/tests/test_coint.py::test_coint_johansen_0lag tsa/vector_ar/tests/test_coint.py::test_johansen_result_aliases_and_rkt_meth tsa/vector_ar/tests/test_coint.py::TestCointJoh09::test_table_trace tsa/vector_ar/tests/test_coint.py::TestCointJoh25::test_table_trace tsa/vector_ar/tests/test_vecm.py::test_select_coint_rank tsa/vector_ar/tests/test_vecm.py::test_coint_rank_results_summary /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/vecm.py:718: ComplexWarning: Casting complex values to real discards the imaginary part lr2[i] = -t * np.log(1 - a[i]) discrete/tests/test_truncated_model.py::TestHurdlePoissonR::test_predict discrete/tests/test_predict.py::TestNegativeBinomialPPredict::test_predict discrete/tests/test_predict.py::TestNegativeBinomialPPredict::test_influence discrete/tests/test_predict.py::TestGeneralizedPoissonPredict::test_influence /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:5286: UserWarning: using default log-link in get_prediction res = pred.get_prediction( discrete/tests/test_truncated_model.py::test_fit_regularized_converged_reports_joint_fit_too /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/l1_slsqp.py:129: ConvergenceWarning: QC check did not pass for 1 out of 2 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers passed = l1_solvers_common.qc_results( discrete/tests/test_truncated_model.py: 13 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:4341: RuntimeWarning: invalid value encountered in log + a1 * np.log(a1) discrete/tests/test_truncated_model.py: 12 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:4343: RuntimeWarning: invalid value encountered in log - (y + a1) * np.log(a2) discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-poisson] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-poisson] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-poisson] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-poisson] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:4380: RuntimeWarning: invalid value encountered in log dgterm = dgpart + np.log(a1 / a2) + 1 - a3 / a2 discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-poisson] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:4841: RuntimeWarning: overflow encountered in exp return np.exp(linpred) discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-poisson] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[poisson-negbin] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:4342: RuntimeWarning: divide by zero encountered in log + y * np.log(mu) discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-poisson] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[poisson-negbin] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:4377: RuntimeWarning: invalid value encountered in divide a4 = p * a1 / mu discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-poisson] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:4380: RuntimeWarning: divide by zero encountered in log dgterm = dgpart + np.log(a1 / a2) + 1 - a3 / a2 discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-poisson] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:4383: RuntimeWarning: invalid value encountered in multiply dparams = a4 * dgterm - a3 / a2 + y / mu discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-poisson] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:4383: RuntimeWarning: divide by zero encountered in divide dparams = a4 * dgterm - a3 / a2 + y / mu discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-poisson] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:4383: RuntimeWarning: overflow encountered in divide dparams = a4 * dgterm - a3 / a2 + y / mu discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-poisson] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:4488: RuntimeWarning: invalid value encountered in log lprob = np.log(prob) discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[poisson-negbin] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:4342: RuntimeWarning: invalid value encountered in multiply + y * np.log(mu) discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[negbin-negbin] discrete/tests/test_truncated_model.py::test_fit_accepts_start_params_split_across_components[poisson-negbin] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:4383: RuntimeWarning: invalid value encountered in divide dparams = a4 * dgterm - a3 / a2 + y / mu discrete/tests/test_truncated_model.py::TestHurdleL1Compatibility::test_t_test /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/discrete_model.py:1436: RuntimeWarning: overflow encountered in exp return -np.exp(XB) + endog * XB - gammaln(endog + 1) discrete/tests/test_truncated_model.py::TestHurdleL1Compatibility::test_t_test /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/discrete/truncated_model.py:742: RuntimeWarning: divide by zero encountered in log np.log(1 - np.exp(llf_main[self.nonzero_idx]))) tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_em_nonstationary tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_em_nonstationary /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/genmod/generalized_linear_model.py:962: RuntimeWarning: divide by zero encountered in scalar divide return np.sum(resid / self.family.variance(mu)) / self.df_resid tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_em_nonstationary /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/dynamic_factor_mq.py:2656: ConvergenceWarning: EM reached maximum number of iterations (2), without achieving convergence: llf=-23.123, convergence criterion=1.8362 (while specified tolerance was 1e-06) results = self.fit_em( stats/tests/test_contingency_tables.py::TestStratified1::test_pandas /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/contingency_tables.py:1263: RuntimeWarning: divide by zero encountered in divide 1 / e11 stats/tests/test_contingency_tables.py::TestStratified1::test_pandas /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/contingency_tables.py:1264: RuntimeWarning: divide by zero encountered in divide + 1 / (self._apc - e11) stats/tests/test_contingency_tables.py::TestStratified1::test_pandas /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/contingency_tables.py:1265: RuntimeWarning: divide by zero encountered in divide + 1 / (self._apb - e11) stats/tests/test_contingency_tables.py::TestStratified1::test_pandas /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/contingency_tables.py:1263: RuntimeWarning: invalid value encountered in add 1 / e11 stats/tests/test_contingency_tables.py::TestStratified1::test_pandas /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/contingency_tables.py:1266: RuntimeWarning: divide by zero encountered in divide + 1 / (self._dma + e11) stats/tests/test_contingency_tables.py::TestStratified1::test_pandas /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/contingency_tables.py:1270: RuntimeWarning: invalid value encountered in divide statistic = np.sum((table[0, 0, :] - e11) ** 2 / v11) tsa/statespace/tests/test_sarimax.py::test_sarimax_starting_values_few_obsevations /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/mlemodel.py:679: EstimationWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters. start_params = self.start_params tsa/statespace/tests/test_sarimax.py::test_plot_too_few_obs /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/mlemodel.py:1461: RuntimeWarning: invalid value encountered in divide return np.inner(score_obs, score_obs) / ( tsa/tests/test_ar.py: 516 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:303: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. index = pd.date_range(dt.datetime(1999, 12, 31), periods=nobs, freq=MONTH_END) tsa/tests/test_ar.py: 126 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:53: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. idx = pd.date_range(dt.datetime(1900, 1, 1), freq=MONTH_END, periods=nobs) tsa/tests/test_ar.py::test_forecast_start_end_equiv[False] tsa/tests/test_ar.py::test_forecast_start_end_equiv[True] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:997: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. y, index=pd.date_range(dt.datetime(1950, 1, 1), periods=1001, freq=MONTH_END) tsa/tests/test_ar.py::test_forecast_start_end_equiv[False] tsa/tests/test_ar.py::test_forecast_start_end_equiv[True] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:1002: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. dates = pd.date_range(dt.datetime(1950, 1, 1), periods=1021, freq=MONTH_END) tsa/tests/test_ar.py: 25 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:1273: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. index = pd.date_range( tsa/tests/test_ar.py::test_autoreg_resids /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:1078: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. idx = pd.date_range(dt.datetime(1900, 1, 1), periods=250, freq=MONTH_END) tsa/tests/test_ar.py::test_predict_seasonal /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:875: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. index=pd.date_range(dt.datetime(1950, 1, 1), periods=1001, freq=MONTH_END), tsa/tests/test_ar.py::test_predict_seasonal /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:890: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. direct, index=pd.date_range(ys.index[900], periods=201, freq=MONTH_END) tsa/tests/test_ar.py::test_predict_seasonal /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:897: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. direct, index=pd.date_range(ys.index[900], periods=101, freq=MONTH_END) tsa/tests/test_ar.py::test_equiv_dynamic /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:826: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. idx = pd.date_range(dt.datetime(2000, 1, 30), periods=1001, freq=MONTH_END) tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/ar_model.py:684: RuntimeWarning: invalid value encountered in matmul forecasts[i] = np.squeeze(new_x[i : i + 1] @ params) tsa/tests/test_ar.py::test_ar_order_select /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:739: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. index=date_range(start=dt.datetime(1990, 1, 1), periods=100, freq=MONTH_END), tsa/tests/test_ar.py::test_predict_irregular_ar /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:960: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. y, index=pd.date_range(dt.datetime(1950, 1, 1), periods=1001, freq=MONTH_END) tsa/tests/test_ar.py::test_predict_irregular_ar /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:976: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. direct, index=pd.date_range(ys.index[900], periods=201, freq=MONTH_END) tsa/tests/test_ar.py::test_predict_irregular_ar /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:982: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. idx = pd.date_range(ys.index[900], periods=101, freq=MONTH_END) tsa/tests/test_ar.py::test_predict_exog /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:912: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. index=pd.date_range(dt.datetime(1950, 1, 1), periods=1001, freq=MONTH_END), tsa/tests/test_ar.py::test_predict_exog /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:927: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. idx = pd.date_range(ys.index[900], periods=101, freq=MONTH_END) tsa/tests/test_ar.py::test_predict_exog /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_ar.py:947: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. direct, index=pd.date_range(ys.index[900], periods=201, freq=MONTH_END) tsa/forecasting/tests/test_stl.py::test_smoke /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/forecasting/tests/test_stl.py:25: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. index = pd.date_range("1980-1-1", freq=MONTH_END, periods=500) base/tests/test_penalized.py::TestPenalizedGLMBinomCountOracleHC2::test_summary base/tests/test_penalized.py::TestPenalizedGLMBinomCountOracleHC::test_numdiff /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/genmod/generalized_linear_model.py:1342: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals rslt = super().fit( tsa/arima/estimators/tests/test_estimator_result.py::test_gls_returns_estimator_result /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/arima/estimators/tests/test_estimator_result.py:56: ConvergenceWarning: Feasible GLS failed to converge in 2 iterations. Consider increasing the maximum number of iterations using the `max_iter` argument or reducing the required tolerance using the `tolerance` argument. _check(gls(endog, exog, order=(1, 0, 0), max_iter=2)) duration/tests/test_survfunc.py::test_kernel_survfunc3 /usr/lib/python3.14/site-packages/numpy/_core/numeric.py:475: RuntimeWarning: invalid value encountered in cast multiarray.copyto(res, fill_value, casting='unsafe') graphics/tests/test_tsaplots.py::test_plot_quarter /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:379: FutureWarning: 'Q-Oct' is deprecated and will be removed in a future version, please use 'Q-OCT' instead. dta.set_index(pd.PeriodIndex(dates, freq=FREQ), inplace=True) graphics/tests/test_tsaplots.py::test_plot_quarter /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:384: FutureWarning: 'Q-Oct' is deprecated and will be removed in a future version, please use 'Q-OCT' instead. dta.index = pd.PeriodIndex(dates, freq=FREQ).to_timestamp(freq=FREQ) graphics/tests/test_tsaplots.py::test_predict_plot[0.1-True-model_and_args1] graphics/tests/test_tsaplots.py::test_predict_plot[0.1-True-model_and_args0] graphics/tests/test_tsaplots.py::test_predict_plot[None-True-model_and_args0] graphics/tests/test_tsaplots.py::test_predict_plot[None-True-model_and_args1] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:439: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. index = pd.date_range("1960-1-1", freq=MONTH_END, periods=y.shape[0] + 24) graphics/tests/test_tsaplots.py::test_predict_plot[0.1-True-model_and_args1] graphics/tests/test_tsaplots.py::test_predict_plot[0.1-True-model_and_args1] graphics/tests/test_tsaplots.py::test_predict_plot[0.1-True-model_and_args0] graphics/tests/test_tsaplots.py::test_predict_plot[0.1-True-model_and_args0] graphics/tests/test_tsaplots.py::test_predict_plot[None-True-model_and_args0] graphics/tests/test_tsaplots.py::test_predict_plot[None-True-model_and_args0] graphics/tests/test_tsaplots.py::test_predict_plot[None-True-model_and_args1] graphics/tests/test_tsaplots.py::test_predict_plot[None-True-model_and_args1] /usr/lib/python3.14/site-packages/pandas/plotting/_matplotlib/converter.py:1063: MatplotlibDeprecationWarning: The locs attribute was deprecated in Matplotlib 3.11 and will be removed in 3.13. self.locs: list[Any] = [] # unused, for matplotlib compat graphics/tests/test_tsaplots.py: 16 warnings /usr/lib/python3.14/site-packages/pandas/plotting/_matplotlib/converter.py:1087: MatplotlibDeprecationWarning: The locs attribute was deprecated in Matplotlib 3.11 and will be removed in 3.13. self.locs = locs graphics/tests/test_tsaplots.py: 10 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/graphics/tests/test_tsaplots.py:454: DeprecationWarning: The 'generic' unit for NumPy timedelta is deprecated, and will raise an error in the future. This includes implicit conversion of bare integers (e.g. `+ 1`). Please use a specific unit instead. idx = [pd.Timestamp.now() + pd.Timedelta(seconds=i) for i in range(10)] tsa/base/tests/test_prediction.py: 14 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/base/tests/test_prediction.py:17: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. idx = pd.date_range("2000-1-1", periods=10, freq=MONTH_END) tsa/base/tests/test_base.py::test_keyerror_start_date /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/base/tests/test_base.py:71: FutureWarning: 'A-APR' is deprecated and will be removed in a future version, please use 'YE-APR' instead. dates = pd.date_range("1972-4-30", "2006-4-30", freq=YE_APR) tsa/base/tests/test_base.py::test_predict_freq /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/base/tests/test_base.py:49: FutureWarning: 'A-APR' is deprecated and will be removed in a future version, please use 'YE-APR' instead. dates = pd.date_range("1972-4-30", "2006-4-30", freq=YE_APR) tsa/base/tests/test_base.py::test_predict_freq /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/base/tests/test_base.py:62: FutureWarning: 'A-APR' is deprecated and will be removed in a future version, please use 'YE-APR' instead. expected_dates = pd.date_range("2006-4-30", "2016-4-30", freq=YE_APR) stats/tests/test_descriptivestats.py::test_empty_columns stats/tests/test_descriptivestats.py::test_empty_columns stats/tests/test_descriptivestats.py::test_categorical_ntop_freq_length stats/tests/test_descriptivestats.py::test_description_basic /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/descriptivestats.py:436: SmallSampleWarning: One or more sample arguments is too small; all returned values will be NaN. See documentation for sample size requirements. mode_res = stats.mode(ser_no_missing, **kwargs) tsa/tests/test_exponential_smoothing.py: 284 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_exponential_smoothing.py:254: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. index = pd.date_range("1999-01-01", "2015-12-31", freq=QUARTER_END) tsa/tests/test_exponential_smoothing.py::test_seasonal_order[heuristic] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/exponential_smoothing/ets.py:1432: RuntimeWarning: invalid value encountered in divide self.standardized_forecasts_error = ( tsa/tests/test_exponential_smoothing.py::test_hessian /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_exponential_smoothing.py:734: PrecisionWarning: Calculation of the Hessian using finite differences is usually subject to substantial approximation errors. fit.model.hessian( tsa/tests/test_exponential_smoothing.py::test_seasonal_order[estimated] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/exponential_smoothing/ets.py:1027: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals mlefit = super().fit( nonparametric/tests/test_lowess.py::TestLowess::test_exog_predict /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/nonparametric/tests/test_lowess.py:270: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy y[[5, 6]] = np.nan nonparametric/tests/test_lowess.py::TestLowess::test_exog_predict /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/nonparametric/tests/test_lowess.py:271: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy x[3] = np.nan nonparametric/tests/test_lowess.py::TestLowess::test_duplicate_xs /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/nonparametric/smoothers_lowess.py:237: RuntimeWarning: invalid value encountered in divide res, _ = _lowess( tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[3-factor_orders3-1-True] tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[3-factor_orders3-1-True] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py:193: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. dta_Q = dta_Q.resample(QUARTER_END).last() tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py: 4 warnings tsa/statespace/tests/test_news.py: 51 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/news.py:471: FutureWarning: The previous implementation of stack is deprecated and will be removed in a future version of pandas. See the What's New notes for pandas 2.1.0 for details. Specify future_stack=True to adopt the new implementation and silence this warning. s = self.weights.stack(level=[0, 1], **FUTURE_STACK) regression/tests/test_dimred.py::test_covreduce /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/regression/tests/test_dimred.py:213: ConvergenceWarning: CovReduce optimization did not converge, |g|=1.287955 rslt = cr.fit() distributions/copula/tests/test_model.py::TestGaussian::test distributions/copula/tests/test_model.py::TestClayton::test distributions/copula/tests/test_model.py::TestEVAsymLogistic::test distributions/copula/tests/test_model.py::TestEVAsymMixed::test distributions/copula/tests/test_model.py::TestEVHR::test distributions/copula/tests/test_model.py::TestFrank::test distributions/copula/tests/test_model.py::TestGumbel::test /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/model.py:1200: UserWarning: df_model + k_constant + k_extra differs from k_params genericmlefit = results_class(self, mlefit) distributions/copula/tests/test_model.py::TestGaussian::test distributions/copula/tests/test_model.py::TestClayton::test distributions/copula/tests/test_model.py::TestEVAsymLogistic::test distributions/copula/tests/test_model.py::TestEVAsymMixed::test distributions/copula/tests/test_model.py::TestEVHR::test distributions/copula/tests/test_model.py::TestFrank::test distributions/copula/tests/test_model.py::TestGumbel::test /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/model.py:1200: UserWarning: df_resid differs from nobs - k_params genericmlefit = results_class(self, mlefit) base/tests/test_generic_methods.py::TestWaldAnovaRankDeficient::test_interaction_df_less_than_nominal base/tests/test_generic_methods.py::TestWaldAnovaRankDeficient::test_df_rank_adjusted /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/model.py:2269: ValueWarning: covariance of constraints does not have full rank. The number of constraints is 4, but rank is 1 wt = result.wald_test(constraint, scalar=scalar) base/tests/test_generic_methods.py::TestWaldAnovaRankDeficient::test_df_rank_adjusted /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/base/tests/test_generic_methods.py:941: ValueWarning: covariance of constraints does not have full rank. The number of constraints is 4, but rank is 1 wt = res.wald_test(constraint, scalar=True) robust/tests/test_tools.py::test_tuning_smoke[case5] robust/tests/test_tools.py::test_tuning_smoke[case6] /usr/lib/python3.14/site-packages/scipy/stats/_distn_infrastructure.py:3049: IntegrationWarning: The maximum number of subdivisions (50) has been achieved. If increasing the limit yields no improvement it is advised to analyze the integrand in order to determine the difficulties. If the position of a local difficulty can be determined (singularity, discontinuity) one will probably gain from splitting up the interval and calling the integrator on the subranges. Perhaps a special-purpose integrator should be used. cd = integrate.quad(fun, c, d, **kwds)[0] tsa/statespace/tests/test_impulse_responses.py::test_pandas_multivariate_dateindex /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_impulse_responses.py:890: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. ix = pd.date_range(start="2000", periods=1, freq=MONTH_END) tsa/statespace/tests/test_impulse_responses.py::test_pandas_anchor /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_impulse_responses.py:903: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. ix = pd.date_range(start="2000", periods=10, freq=MONTH_END) tsa/statespace/tests/test_impulse_responses.py::test_pandas_univariate_dateindex /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_impulse_responses.py:865: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. ix = pd.date_range(start="2000", periods=1, freq=MONTH_END) tsa/forecasting/tests/test_theta.py::test_plot_predict /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/forecasting/theta.py:686: UserWarning: No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument. ax.legend(loc="best", frameon=False) tsa/statespace/tests/test_simulate.py::test_pandas_anchor /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_simulate.py:2079: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. ix = pd.date_range(start="2000", periods=2, freq=MONTH_END) tsa/statespace/tests/test_simulate.py::test_pandas_multivariate_dateindex_repetitions /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_simulate.py:2047: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. ix = pd.date_range(start="2000", periods=2, freq=MONTH_END) tsa/statespace/tests/test_simulate.py::test_pandas_multivariate_dateindex_repetitions /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_simulate.py:2069: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. ix = pd.date_range(start="2000-03", periods=2, freq=MONTH_END) tsa/statespace/tests/test_simulate.py::test_pandas_multivariate_dateindex /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_simulate.py:2025: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. ix = pd.date_range(start="2000", periods=2, freq=MONTH_END) tsa/statespace/tests/test_simulate.py::test_pandas_multivariate_dateindex /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_simulate.py:2039: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. ix = pd.date_range(start="2000-03", periods=2, freq=MONTH_END) tsa/statespace/tests/test_simulate.py::test_pandas_univariate_dateindex_repetitions /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_simulate.py:1944: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. ix = pd.date_range(start="2000", periods=2, freq=MONTH_END) tsa/statespace/tests/test_simulate.py::test_pandas_univariate_dateindex_repetitions /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_simulate.py:1953: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. ix = pd.date_range(start="2000-01", periods=2, freq=MONTH_END) tsa/statespace/tests/test_simulate.py::test_pandas_univariate_dateindex_repetitions /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_simulate.py:1963: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. ix = pd.date_range(start="2000-03", periods=2, freq=MONTH_END) tsa/statespace/tests/test_simulate.py::test_pandas_univariate_dateindex /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_simulate.py:1921: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. ix = pd.date_range(start="2000", periods=2, freq=MONTH_END) tsa/statespace/tests/test_simulate.py::test_pandas_univariate_dateindex /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_simulate.py:1928: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. ix = pd.date_range(start="2000-01", periods=2, freq=MONTH_END) tsa/statespace/tests/test_simulate.py::test_pandas_univariate_dateindex /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/tests/test_simulate.py:1937: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. ix = pd.date_range(start="2000-03", periods=2, freq=MONTH_END) discrete/tests/test_predict.py::test_distr[case9] discrete/tests/test_predict.py::test_distr[case10] discrete/tests/test_predict.py::test_distr[case11] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/outliers_influence.py:655: RuntimeWarning: invalid value encountered in sqrt return sf / np.sqrt(hf) / np.sqrt(1 - self.hat_matrix_diag) tsa/tests/test_arima_process.py::test_from_estimation[True-0] tsa/tests/test_arima_process.py::test_from_estimation[True-1] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/tests/test_arima_process.py:467: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead. idx = pd.date_range(dt.datetime(1900, 1, 1), periods=500, freq=QUARTER_END) tsa/vector_ar/tests/test_var.py::test_irf_err_bands tsa/vector_ar/tests/test_var.py::test_irf_err_bands /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/irf.py:878: ComplexWarning: Casting complex values to real discards the imaginary part W[i, j, :, :], eigva[i, j, :, 0], k[i, j] = util.eigval_decomp( tsa/vector_ar/tests/test_var.py::test_irf_err_bands /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/vector_ar/irf.py:817: ComplexWarning: Casting complex values to real discards the imaginary part W[i], eigva[i], k[i] = util.eigval_decomp(stack_cov[i]) tsa/vector_ar/tests/test_var.py::TestVARResultsLutkepohl::test_cum_irf_stderr /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/base/tsa_model.py:606: FutureWarning: 'BQ-MAR' is deprecated and will be removed in a future version, please use 'BQE-MAR' instead. freq = to_offset(freq) nonparametric/tests/test_kde.py::test_entropy_finite_domain_kernel[epa] nonparametric/tests/test_kde.py::test_entropy_finite_domain_kernel[tri] nonparametric/tests/test_kde.py::test_entropy_finite_domain_kernel[cos] nonparametric/tests/test_kde.py::test_entropy_finite_domain_kernel[biw] nonparametric/tests/test_kde.py::test_entropy_finite_domain_kernel[uni] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/nonparametric/kde.py:287: IntegrationWarning: The maximum number of subdivisions (50) has been achieved. If increasing the limit yields no improvement it is advised to analyze the integrand in order to determine the difficulties. If the position of a local difficulty can be determined (singularity, discontinuity) one will probably gain from splitting up the interval and calling the integrator on the subranges. Perhaps a special-purpose integrator should be used. return -integrate.quad(entr, a, b, args=(endog,))[0] duration/tests/test_phreg.py::TestPHReg::test_predict_formula /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/duration/tests/test_phreg.py:215: SpecificationWarning: PHReg formulas should not include any '0' or '1' terms model1 = PHReg.from_formula(fml, df, status=status) stats/tests/test_corrpsd.py::TestCorrPSD1::test_nearest /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/tests/test_corrpsd.py:226: IterationLimitWarning: Maximum iteration reached. y = corr_nearest(x, threshold=1e-7, n_fact=100) stats/tests/test_corrpsd.py::TestCovPSD::test_cov_nearest stats/tests/test_corrpsd.py::test_corrpsd_threshold[1e-06] stats/tests/test_corrpsd.py::test_corrpsd_threshold[1e-15] stats/tests/test_corrpsd.py::test_corrpsd_threshold[1e-10] stats/tests/test_corrpsd.py::test_corrpsd_threshold[0] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/correlation_tools.py:291: IterationLimitWarning: Maximum iteration reached. corr_ = corr_nearest(cov_, threshold=threshold, n_fact=n_fact) stats/tests/test_corrpsd.py::test_corrpsd_threshold[1e-06] stats/tests/test_corrpsd.py::test_corrpsd_threshold[1e-15] stats/tests/test_corrpsd.py::test_corrpsd_threshold[1e-10] stats/tests/test_corrpsd.py::test_corrpsd_threshold[0] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/stats/tests/test_corrpsd.py:377: IterationLimitWarning: Maximum iteration reached. y = corr_nearest(x, n_fact=100, threshold=threshold) tsa/stl/tests/test_mstl.py::test_number_of_seasonal_components[data-periods2-None-2] tsa/stl/tests/test_mstl.py::test_output_invariant_to_period_order[data-periods_ordered1-windows_ordered1-periods_not_ordered1-windows_not_ordered1] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/stl/mstl.py:125: UserWarning: A period(s) is larger than half the length of time series. Removing these period(s). self.periods, self.windows = self._process_periods_and_windows(periods, windows) tsa/statespace/tests/test_news.py: 40 warnings /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/news.py:650: FutureWarning: The previous implementation of stack is deprecated and will be removed in a future version of pandas. See the What's New notes for pandas 2.1.0 for details. Specify future_stack=True to adopt the new implementation and silence this warning. s = self.weights.stack(level=[0, 1], **FUTURE_STACK) tsa/statespace/tests/test_news.py::test_detailed_revisions[True] tsa/statespace/tests/test_news.py::test_grouped_revisions[202] tsa/statespace/tests/test_news.py::test_mixed_revisions[201] tsa/statespace/tests/test_news.py::test_grouped_revisions[False] tsa/statespace/tests/test_news.py::test_detailed_revisions[-10] tsa/statespace/tests/test_news.py::test_detailed_revisions[200] tsa/statespace/tests/test_news.py::test_mixed_revisions[-1] /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/news.py:738: FutureWarning: The previous implementation of stack is deprecated and will be removed in a future version of pandas. See the What's New notes for pandas 2.1.0 for details. Specify future_stack=True to adopt the new implementation and silence this warning. weights = self.revision_weights.stack(level=[0, 1], **FUTURE_STACK) tsa/statespace/tests/test_news.py::test_news_summary_methods tsa/statespace/tests/test_news.py::test_news_summary_methods tsa/statespace/tests/test_news.py::test_news_summary_methods tsa/statespace/tests/test_news.py::test_news_summary_methods tsa/statespace/tests/test_news.py::test_news_summary_methods tsa/statespace/tests/test_news.py::test_news_summary_methods /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/statespace/news.py:569: FutureWarning: The previous implementation of stack is deprecated and will be removed in a future version of pandas. See the What's New notes for pandas 2.1.0 for details. Specify future_stack=True to adopt the new implementation and silence this warning. weights = self.revision_weights.stack(level=[0, 1], **FUTURE_STACK) tsa/stl/tests/test_stl.py::test_squezable_to_1d /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/stl/tests/test_stl.py:337: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. data = data.resample(MONTH_END).mean().ffill() tsa/stl/tests/test_stl.py::test_period_detection /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/statsmodels/tsa/stl/tests/test_stl.py:274: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead. index = pd.date_range("1-1-1959", periods=348, freq=MONTH_END) -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html - generated xml file: /startdir/src/statsmodels/test-env/lib/python3.14/site-packages/test-data.xml - ============================= slowest 30 durations ============================= 28.67s call stats/tests/test_knockoff.py::test_sim[tester3-3000-200-3.5-equi] 16.41s call tsa/tests/test_stattools.py::TestZivotAndrews::test_rand10000_case 13.71s call tsa/vector_ar/tests/test_var.py::test_irf_err_bands 10.36s call stats/tests/test_mediation.py::test_framing_example_formula 10.04s call emplike/tests/test_regression.py::TestRegressionPowell::test_ci_beta0 9.24s call regression/tests/test_processreg.py::test_formulas[True] 8.75s call tsa/tests/test_exponential_smoothing.py::test_prediction_results_slow_AAdA 7.90s call graphics/tests/test_functional.py::test_hdr_multiple_alpha 7.56s call emplike/tests/test_aft.py::Test_AFTModel::test_betaci 7.56s call robust/tests/test_tools.py::test_eff[case7] 7.40s call tsa/statespace/tests/test_sarimax.py::test_concentrated_scale 7.06s call regression/tests/test_processreg.py::test_arrays[True] 6.76s call stats/tests/test_corrpsd.py::Test_Factor::test_corr_nearest_factor_sparse[2] 6.47s call robust/tests/test_tools.py::test_eff[case6] 6.29s call tests/test_package.py::test_docstring_optimization_compat 6.01s setup discrete/tests/test_truncated_model.py::TestHurdleL1Compatibility::test_t_test 5.95s call emplike/tests/test_regression.py::TestRegressionPowell::test_ci_beta2 5.87s call graphics/tests/test_functional.py::test_hdr_threshold 5.83s call graphics/tests/test_functional.py::test_hdr_alpha 5.77s call regression/tests/test_processreg.py::test_formulas[False] 5.66s call tsa/tests/test_exponential_smoothing.py::test_prediction_results_slow_AAN 5.56s call discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_minimize 5.49s call regression/tests/test_processreg.py::test_arrays[False] 5.23s call emplike/tests/test_regression.py::TestRegressionPowell::test_ci_beta1 5.20s call stats/tests/test_corrpsd.py::Test_Factor::test_corr_nearest_factor_sparse[1] 5.04s call stats/tests/test_mediation.py::test_framing_example_moderator_formula 4.56s call graphics/tests/test_functional.py::test_hdr_basic 4.46s call graphics/tests/test_functional.py::test_hdr_ncomp 4.40s call gam/tests/test_penalized.py::TestGAMMPGBSPoisson::test_select_alpha 4.32s call gam/tests/test_penalized.py::TestGAMMPGBSPoissonFormula::test_select_alpha =========================== short test summary info ============================ FAILED statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period7] - KeyError: 'ME' FAILED statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period12] - KeyError: 'ME' FAILED statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period11] - KeyError: 'QE' FAILED statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[None-freq_period9] - KeyError: 'ME' FAILED statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period9] - KeyError: 'ME' FAILED statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period7] - KeyError: 'ME' FAILED statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period11] - KeyError: 'QE' FAILED statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[False-freq_period12] - KeyError: 'ME' FAILED statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period9] - KeyError: 'ME' FAILED statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period12] - KeyError: 'ME' FAILED statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period11] - KeyError: 'QE' FAILED statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonality[list-freq_period7] - KeyError: 'ME' FAILED statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonal_period_a - KeyError: 'ME' FAILED statsmodels/tsa/tests/test_deterministic.py::test_calendar_seasonal_period_q - KeyError: 'ME' = 14 failed, 20858 passed, 365 skipped, 145 xfailed, 111865 warnings in 849.64s (0:14:09) = ==> ERROR: A failure occurred in check(). Aborting... ==> ERROR: Build failed, check /home/alhp/workspace/chroot/build_cf32b644-9579-4056-acc9-06524d6cb1d3/build