scikits.statsmodels is a Python library that provides a complement to scipy for statistical computations including descriptive statistics and estimation of statistical models.
scikits.statsmodels provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for six distribution families, M-estimators for robust linear models, and regression with discrete dependent variables, Logit, Probit, MNLogit, Poisson, based on maximum likelihood estimators, timeseries models, ARMA, AR and VAR. An extensive list of result statistics are available for each estimation problem. Statsmodels also contains descriptive statistics, a wide range of statistical tests and more.
We welcome feedback: mailing list at http://groups.google.com/group/pystatsmodels or our bug tracker at https://bugs.launchpad.net/statsmodels
For updated versions between releases, we recommend our repository at http://code.launchpad.net/statsmodels We will move to github in the near future https://github.com/statsmodels
- The only change compared to 0.4.2 is for compatibility with python 3.2.3 (changed behavior of 2to3).