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