statsmodels is an excellent project and important part of the python scientific stack. But due to resource constraints, they cannot push out bugfixes often enough for my needs. sm2 is a fork focused on bugfixes and addressing technical debt.

Ideally sm2 will be a drop-in replacement for statsmodels. In places where this fails, feel free to open an issue.

With luck, fixes made here will eventually be ported upstream.

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• sm2 contains a subset of the functionality of statsmodels. The first big difference is that statsmodels is more feature-complete.

• Test coverage statistics reported for sm2 are meaningful (:issue:4331)

• An enormous amount of code-cleanup has been done in sm2. Thousands of lines of unused, untested, or deprecated code have been removed. Many thousands of flake8 formatting issues have been cleaned up.

• MultinomialResults.params and predict will have correct column and row labels (:issue:4541)

• VARResults.cov_params will correctly return a DataFrame instead of raising ValueError.

• VARResults.acf will return correct results (:issue:4572)

• The ArmaProcess class does not have a nobs attribute.

• tsa.stattools.acf will always return (acf, confint, qstat, pvalue) here instead of a different subset of these depending on the inputs.

• stats.diagnostic.acorr_ljungbox will always return (qljungbox, pval, qboxpierce, pvalbp) here instead of a different subset of these depending on the inputs.

• summary2 methods have not been ported from upstream, will raise NotImplementedError.

• VARResults.test_whiteness has been superceeded upstream by test_whiteness_new as the older method was not an actual statistical test (:issue:4036). sm2 replaces the older version entirely and keeps only the name test_whiteness.

• ARModel.fit incorrectly sets model.df_resid upstream. That has been fixed here.

• GenericLikelihoodModelResults.__init__ incorrectly sets model.df_resid and model.df_model. That has been fixed here.

• GeneralizedLinearModel.fit incorrect sets self.mu and self.scale. This has been fixed here. (:issue:4032)

• LikelihoodModelResults._get_robustcov_results incorrectly ignores use_self argument. This has been fixed here. (:issue:4401)

Issues and Pull Requests are welcome. If you are looking a place to start, here are some suggestions:

• Search for comments starting with # TODO: or # FIXME:

  • Some comments are copied from upstream and should have these labels but are missing them. If you find a comment that should have one of these labels (or is just unclear), add the label.

• Many tests from upstream are marked with pytest.mark.not_vetted to reflect the fact that they haven't been reviewed since being ported from statsmodels. To "vet" a test, try to determine:

  • Is this a "smoke test"? If so, it should be marked with pytest.mark.smoke.
  • Is this a test for a specific bug? Can an Issue reference (e.g. # GH#1234) be included?
  • Is there something specific being tested? If so, the test name should be made informative and often a comment should be added (e.g. # test function foo.bar in case where baz argument is near-singular)
  • Is this testing results produced by statsmodels/sm2 against results produced by another package? If so, it should be clear how those results were produced. The original authors put a lot of effort into producing these comparisons; they should be reproducible.

• There are some spots where tests are meager and could use some attention:

  • tsa.vector_ar.irf
  • regression._prediction
  • stats.sandwich_covariance

• As of 2018-03-19 there are still 390 flake8 warnings/errors. For many of these, fixing them requires figuring out what the writer's attention was upstream.

• As of 2018-03-19 about 20% of statsmodels has been ported to sm2 (though a much larger percentage of the usable, non-redundant, non-deprecated code). If there are portions of statsmodels that you want or need, don't be shy.

• If there is a change you parrticularly like, make a Pull Request upstream to get it implemented directly in statsmodels.