24 lines
1.3 KiB
Text
24 lines
1.3 KiB
Text
Statsmodels is a Python package that provides a complement to scipy for
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statistical computations including descriptive statistics and estimation and
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inference for statistical models.
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Main Features:
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* linear regression models: GLS (including WLS and LS aith AR errors) and OLS.
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* glm: Generalized linear models with support for all of the one-parameter
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exponential family distributions.
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* discrete: regression with discrete dependent variables, including Logit,
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Probit, MNLogit, Poisson, based on maximum likelihood estimators
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* rlm: Robust linear models with support for several M-estimators.
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* tsa: models for time series analysis - univariate: AR, ARIMA; multivariate:
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VAR and structural VAR
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* nonparametric: (Univariate) kernel density estimators
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* datasets: Datasets to be distributed and used for examples and in testing.
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* stats: a wide range of statistical tests, diagnostics and specification tests
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* iolib: Tools for reading Stata .dta files into numpy arrays, printing table
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output to ascii, latex, and html
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* miscellaneous models
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* sandbox: statsmodels contains a sandbox folder with code in various stages of
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* developement and testing which is not considered "production ready", including
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Mixed models, GARCH and GMM estimators, kernel regression, panel data models.
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WWW: https://github.com/statsmodels/statsmodels
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