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non port: head/math/py-statsmodels/pkg-plist
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Number of commits found: 4

Fri, 22 May 2015
[ 04:37 xmj ] Original commit   Revision:386983
386983 math/py-statsmodels/Makefile
386983 math/py-statsmodels/distinfo
386983 math/py-statsmodels/pkg-plist
math/py-statsmodels: switch to GitHub, clean up stuff

- switch upstream to GitHub
- as there is no new release available, bump PORTREVISION
- remove Sphinx build from docs option, due to recursive imports.
Tue, 9 Dec 2014
[ 17:33 xmj ] Original commit   Revision:374411
374411 math/py-statsmodels/Makefile
374411 math/py-statsmodels/distinfo
374411 math/py-statsmodels/pkg-plist
math/py-statsmodels: update to 0.6.1, unbreak, modernize

- update to 0.6.1 and unbreak
- replace noegginfo with concurrent in USE_PYTHON

Differential Revision:	https://reviews.freebsd.org/D1287
Approved by:	swills (mentor)
Fri, 14 Nov 2014
[ 09:39 antoine ] Original commit   Revision:372555
372555 lang/x10/pkg-plist
372555 math/pari/pkg-plist
372555 math/parmgridgen/pkg-plist
372555 math/pdal/pkg-plist
372555 math/pecl-big_int/pkg-plist
372555 math/physcalc/pkg-plist
372555 math/plman/pkg-plist
372555 math/ploticus/pkg-plist
372555 math/plplot/pkg-plist
372555 math/proofgeneral/pkg-plist

(Only the first 10 of 65 ports in this commit are shown above. View all ports for this commit)
Cleanup plist
Fri, 22 Nov 2013
[ 12:40 wg ] Original commit   Revision:334582
334582 math/Makefile
334582 math/py-statsmodels
334582 math/py-statsmodels/Makefile
334582 math/py-statsmodels/distinfo
334582 math/py-statsmodels/pkg-descr
334582 math/py-statsmodels/pkg-plist
math/py-statsmodels: Complement to SciPy for statistical computations

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: GLS (including WLS and LS aith AR errors) and OLS.
* 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: AR, ARIMA; multivariate:
  VAR and structural VAR
(Only the first 15 lines of the commit message are shown above View all of this commit message)

Number of commits found: 4

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