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        "author": "Brock Mendel",
        "author_email": "jbrockmendel@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Environment :: Console",
            "Intended Audience :: Developers",
            "Intended Audience :: End Users/Desktop",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Natural Language :: English",
            "Operating System :: OS Independent",
            "Programming Language :: Cython",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering"
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        "description": "sm2\n---\n[statsmodels](https://github.com/statsmodels/statsmodels) is an excellent\nproject and important part of the python scientific stack.  But due to resource\nconstraints, they cannot push out bugfixes often enough for my needs.  sm2\nis a fork focused on bugfixes and addressing technical debt.\n\nIdeally sm2 will be a drop-in replacement for statsmodels.  In places where\nthis fails, feel free to open an issue.\n\nWith luck, fixes made here will eventually be ported upstream.\n\n\n<table>\n<tr>\n  <td>Build Status</td>\n  <td>\n    <a href=\"https://travis-ci.org/jbrockmendel/sm2\">\n    <img src=\"https://travis-ci.org/jbrockmendel/sm2.svg?branch=master\" alt=\"travis build status\" />\n    </a>\n  </td>\n</tr>\n<tr>\n  <td></td>\n  <td>\n    <a href=\"https://ci.appveyor.com/project/jbrockmendel/sm2\">\n    <img src=\"https://ci.appveyor.com/api/projects/status/gw9cui82oc1lnyqi/branch/master?svg=true\" alt=\"appveyor build status\" />\n    </a>\n  </td>\n</tr>\n<tr>\n  <td>Coverage</td>\n  <td>\n    <a href=\"https://codecov.io/gh/jbrockmendel/sm2\">\n    <img src=\"https://codecov.io/gh/jbrockmendel/sm2/branch/master/graph/badge.svg\" />\n    </a>\n</td>\n</tr>\n</table>\n\n\nChanges vs Statsmodels\n----------------------\n- sm2 contains a subset of the functionality of statsmodels.  The first big\ndifference is that statsmodels is more feature-complete.\n\n- Test coverage statistics reported for sm2 are meaningful (:issue:`4331`)\n\n- An enormous amount of code-cleanup has been done in sm2.  Thousands of lines\nof unused, untested, or deprecated code have been removed.  _Many_ thousands\nof flake8 formatting issues have been cleaned up.\n\n- `MultinomialResults.params` and `predict` will have correct column and row\nlabels (:issue:`4541`)\n\n- `VARResults.cov_params` will correctly return a `DataFrame` instead\nof raising `ValueError`.\n\n- `VARResults.acf` will return correct results (:issue:`4572`)\n\n- The `ArmaProcess` class does not have a `nobs` attribute.\n\n- `tsa.stattools.acf` will always return `(acf, confint, qstat, pvalue)` here\ninstead of a different subset of these depending on the inputs.\n\n- stats.diagnostic.acorr_ljungbox will always return\n`(qljungbox, pval, qboxpierce, pvalbp)` here instead of a different subset\nof these depending on the inputs.\n\n- `summary2` methods have not been ported from upstream, will\nraise `NotImplementedError`.\n\n- `VARResults.test_whiteness` has been superceeded upstream by\n`test_whiteness_new` as the older method was not an actual statistical\ntest (:issue:`4036`).  `sm2` replaces the older version entirely and keeps\nonly the name `test_whiteness`.\n\n- `ARModel.fit` incorrectly sets `model.df_resid` upstream.  That has been\nfixed here.\n\n- `GenericLikelihoodModelResults.__init__` incorrectly sets `model.df_resid`\nand `model.df_model`.  That has been fixed here.\n\n- `GeneralizedLinearModel.fit` incorrect sets `self.mu` and `self.scale`.\nThis has been fixed here.  (:issue:`4032`)\n\n- `LikelihoodModelResults._get_robustcov_results` incorrectly ignores\n`use_self` argument.  This has been fixed here.  (:issue:`4401`)\n\nContributing\n------------\nIssues and Pull Requests are welcome.  If you are looking a place to start,\nhere are some suggestions:\n\n- Search for comments starting with `# TODO:` or `# FIXME:`\n     - Some comments are copied from upstream and _should_ have these labels\n       but are missing them.  If you find a comment that should have one of\n       these labels (or is just unclear), add the label.\n\n- Many tests from upstream are marked with `pytest.mark.not_vetted` to reflect\n  the fact that they haven't been reviewed since being ported from statsmodels.\n  To \"vet\" a test, try to determine:\n    - Is this a \"smoke test\"?  If so, it should be marked with\n      `pytest.mark.smoke`.\n    - Is this a test for a specific bug?  Can an Issue reference\n      (e.g. `# GH#1234`) be included?\n    - Is there something specific being tested?  If so, the test name should\n      be made informative and often a comment should be added\n      (e.g. `# test function foo.bar in case where baz argument is\n      near-singular`)\n    - Is this testing results produced by statsmodels/sm2 against results\n      produced by another package?  If so, it should be clear how those results\n      were produced.  The original authors put a lot of effort into producing\n      these comparisons; they should be reproducible.\n\n- There are some spots where tests are meager and could use some attention:\n    - `tsa.vector_ar.irf`\n    - `regression._prediction`\n    - `stats.sandwich_covariance`\n\n- As of 2018-03-19 there are still 390 flake8 warnings/errors.  For many of\n  these, fixing them requires figuring out what the writer's attention was\n  upstream.\n\n- As of 2018-03-19 about 20% of statsmodels has been ported to sm2 (though a\n  much larger percentage of the usable, non-redundant, non-deprecated code).\n  If there are portions of statsmodels that you want or need, don't be shy.\n\n- If there is a change you parrticularly like, make a Pull Request upstream\n  to get it implemented directly in statsmodels.\n\n\n",
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