Python module for descriptive statistics and estimation of statistical models
Python C Other
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Failed to load latest commit information.
docs DOC: Update release notes with maint branch changes. Aug 14, 2013
examples notebook examples title cell Sep 4, 2013
statsmodels COMPAT: Allow 3.x cached files to be opened in 2.x Aug 20, 2013
tools DOC/BLD: Increase timeout for robust_model notebook. Aug 14, 2013
.bzrignore sandbox Mar 11, 2010
.coveragerc VAR test coverage Jan 31, 2011
.gitattributes add gitattributes (numpy minus .nsi) Jun 12, 2011
.gitignore Maint: gitignore: add dist (./dist doesn't work) Feb 20, 2013
.mailmap MAINT: Fix mailmap entry. Aug 14, 2013
.travis.yml RF: I think coveralls works now so disabling all those pwd debug prin… Sep 12, 2013
.travis_coveragerc BF: since we are testing installed version, do not omit /usr but rath… Sep 12, 2013 DOC: Point to changes in the docs. Jul 31, 2013
CONTRIBUTING.rst GITHUB: Contributing guidlines Jul 30, 2013
COPYRIGHTS.txt Docs: add license for qsturng-py and license notice for ordereddict Apr 8, 2012
INSTALL.txt ENH: Bump Python and NumPy versions. Remove 2.5 only code. Aug 4, 2013
LICENSE.txt DOC: Update copyright dates Apr 1, 2012 BLD: work around problems installing data files in libqsturng Jun 24, 2013
README.txt DOC: very minor (trailing spaces) to trigger travis build Sep 12, 2013
README_l1.txt Updated examples Oct 6, 2012
build_bdists.bat BLD: Create archives in windows build script Jul 16, 2012 BLD: Add setuptools bootstrap script to version control May 4, 2013
setup.cfg changes to, add manifest to make sdist include data files wi… Aug 23, 2009 MAINT: Set isreleased=False. Bump version to 0.6.0 Aug 14, 2013


What Statsmodels is
What it is

Statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics and estimation and inference for statistical models.

Main Features

* linear regression models: Generalized least squares (including weighted least squares and
  least squares with autoregressive errors), ordinary least squares.
* glm: Generalized linear models with support for all of the one-parameter
  exponential family distributions.
* discrete: regression with discrete dependent variables, including Logit, Probit, MNLogit, Poisson, based on maximum likelihood estimators
* rlm: Robust linear models with support for several M-estimators.
* tsa: models for time series analysis
  - univariate time series analysis: AR, ARIMA
  - vector autoregressive models, VAR and structural VAR
  - descriptive statistics and process models for time series analysis
* nonparametric : (Univariate) kernel density estimators
* datasets: Datasets to be distributed and used for examples and in testing.
* stats: a wide range of statistical tests
  - diagnostics and specification tests
  - goodness-of-fit and normality tests
  - functions for multiple testing
  - various additional statistical tests
* iolib
  - Tools for reading Stata .dta files into numpy arrays.
  - printing table output to ascii, latex, and html
* miscellaneous models
* sandbox: statsmodels contains a sandbox folder with code in various stages of
  developement and testing which is not considered "production ready".
  This covers among others Mixed (repeated measures) Models, GARCH models, general method
  of moments (GMM) estimators, kernel regression, various extensions to scipy.stats.distributions,
  panel data models, generalized additive models and information theoretic measures.

Where to get it

The master branch on GitHub is the most up to date code

Source download of release tags are available on GitHub

Binaries and source distributions are available from PyPi

Installation from sources

See INSTALL.txt for requirements or see the documentation


Modified BSD (3-clause)


The official documentation is hosted on SourceForge

Windows Help
The source distribution for Windows includes a htmlhelp file (statsmodels.chm).
This can be opened from the python interpreter ::

    >>> import statsmodels.api as sm
    >>> sm.open_help()

Discussion and Development

Discussions take place on our mailing list.

We are very interested in feedback about usability and suggestions for improvements.

Bug Reports

Bug reports can be submitted to the issue tracker at