What Statsmodels 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.
Change in Location of Documentation
Due to the current outage of our online documentation, we recreated the documentation on GitHub.
The documentation for the latest release is at
The documentation for the development version is at
This is currently a temporary solution that will be transformed into the new permanent location.
- 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
Binaries can be installed in Anaconda
conda install statsmodels
Development snapshots are also avaiable in Anaconda
conda install -c https://conda.binstar.org/statsmodels statsmodels
Installation from sources
See INSTALL.txt for requirements or see the documentation
Modified BSD (3-clause)
The official documentation is hosted on SourceForge
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 can be submitted to the issue tracker at