Commit graph

4 commits

Author SHA1 Message Date
Gerald Pfeifer
15945f8122 Update the default version of GCC in the Ports Collection from GCC 4.7.4
to GCC 4.8.3.

Part II, Bump PORTREVISIONs.

PR:		192025
Tested by:	antoine (-exp runs)
Approved by:	portmgr (implicit)
2014-09-10 20:50:31 +00:00
Antoine Brodin
9daf93ad63 Mark BROKEN: Fails to build
building [html]: targets for 66 source files that are out of date
updating environment: 1739 added, 0 changed, 0 removed
reading sources... [  0%] anova
Traceback (most recent call last):
...
  File "/wrkdirs/usr/ports/math/py-statsmodels/work/statsmodels-0.5.0/docs/sphinxext/ipython_directive.py", line 589, in setup
    store_history=False)
  File "/wrkdirs/usr/ports/math/py-statsmodels/work/statsmodels-0.5.0/docs/sphinxext/ipython_directive.py", line 260, in process_input_line
    source_raw = splitter.source_raw_reset()[1]
AttributeError: 'IPythonInputSplitter' object has no attribute 'source_raw_reset'
*** [do-build] Error code 1

Reported by:	pkg-fallout
2014-06-19 21:40:42 +00:00
Gerald Pfeifer
1cd277bdce Update the default version of GCC used in the Ports Collection from
GCC 4.6.4 to GCC 4.7.3.  This entails updating the lang/gcc port as
well as changing the default in Mk/bsd.default-versions.mk.

Part II, Bump PORTREVISIONs.

PR:		182136
Supported by:	Christoph Moench-Tegeder <cmt@burggraben.net> (fixing many ports)
Tested by:	bdrewery (two -exp runs)
2014-03-10 20:55:20 +00:00
William Grzybowski
01725b54b2 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
* 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
* 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", including
  Mixed models, GARCH and GMM estimators, kernel regression, panel data models.

WWW: https://www.github.com/statsmodels/statsmodels

PR:		ports/183932
Submitted by:	Johannes Jost Meixner <xmj chaot.net>
2013-11-22 12:40:09 +00:00