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What it is ========== Statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics and estimation of statistical models. Main Features ============= * regression: 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 choice models: Poisson, probit, logit, multinomial logit * rlm: Robust linear models with support for several M-estimators. * tsa: Time series analysis models, including ARMA, AR, VAR * nonparametric : (Univariate) kernel density estimators * datasets: Datasets to be distributed and used for examples and in testing. * PyDTA: Tools for reading Stata .dta files into numpy arrays. * stats: a wide range of statistical tests * sandbox: There is also a sandbox which contains code for generalized additive models (untested), mixed effects models, cox proportional hazards model (both are untested and still dependent on the nipy formula framework), generating descriptive statistics, and printing table output to ascii, latex, and html. There is also experimental code for systems of equations regression, time series models, panel data estimators and information theoretic measures. None of this code is considered "production ready". Where to get it =============== Development branches will be on Github. This is where to go to get the most up to date code in the trunk branch. Experimental code is hosted here in branches and in developer forks. This code is merged to master often. We try to make sure that the master branch is always stable. https://www.github.com/statsmodels/statsmodels Source download of stable tags will be on SourceForge. https://sourceforge.net/projects/statsmodels/ or PyPi: http://pypi.python.org/pypi/statsmodels/ Installation from sources ========================= In the top directory, just do:: python setup.py install See INSTALL.txt for requirements or http://statsmodels.sourceforge.net/ For more information. License ======= Simplified BSD Documentation ============= The official documentation is hosted on SourceForge. http://statsmodels.sourceforge.net/ The sphinx docs are currently undergoing a lot of work. They are not yet comprehensive, but should get you started. Our blog will continue to be updated as we make progress on the code. http://scipystats.blogspot.com 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 ========================== All chatter will take place on the or scipy-user mailing list. We are very interested in receiving feedback about usability, suggestions for improvements, and bug reports via the mailing list or the bug tracker at https://github.com/statsmodels/statsmodels/issues There is also a google group at http://groups.google.com/group/pystatsmodels to discuss development and design issues that are deemed to be too specialized for the scipy-dev/user list. Python 3 ======== statsmodels has been ported and tested for Python 3.2. Python 3 version of the code can be obtained by running 2to3.py over the entire statsmodels source. The numerical core of statsmodels worked almost without changes, however there can be problems with data input and plotting. The STATA file reader and writer in iolib.foreign has not been ported yet. And there are still some problems with the matplotlib version for Python 3 that was used in testing. Running the test suite with Python 3.2 shows some errors related to foreign and matplotlib.