Log message:
math/py-statsmodels: Update to 0.11.1

Major Features:

- Allow fixing parameters in state space models
- Add new version of ARIMA-type estimators (AR, ARIMA, SARIMAX)
- Add STL decomposition for time series
- Functional SIR
- Zivot Andrews test
- Added Oaxaca-Blinder Decomposition
- Add rolling WLS and OLS
- Replacement for AR

Performance Improvements:

- Cythonize innovations algo and filter
- Only perform required predict iterations in state space models
- State space: Improve low memory usability; allow in fit, loglike

Log message:
math/py-statsmodels: Update to 0.10.2

This is a major release from 0.9.0 and includes a number new
statistical models and many bug fixes.

Highlights include:

* Generalized Additive Models. This major feature is experimental and
  may change.
* Conditional Models such as ConditionalLogit, which are known as
  fixed effect models in Econometrics.
* Dimension Reduction Methods include Sliced Inverse Regression,
  Principal Hessian Directions and Sliced Avg. Variance Estimation
* Regression using Quadratic Inference Functions (QIF)
* Gaussian Process Regression

Log message:
py-statsmodels: update to 0.9.0nb2.

Remove some .so files from the PLIST that are not built for me
nor in mef's 9.0 bulk build.

Log message:
py-statsmodels: fix for newer SciPy

Log message:
py-statsmodels: updated to 0.9.0

0.9.0:

The Highlights
--------------
statespace refactoring, Markov Switching Kim smoother
3 Google summer of code (GSOC) projects merged - distributed estimation - VECM \ 
and enhancements to VAR (including cointegration test) - new count models: \ 
GeneralizedPoisson, zero inflated models
Bayesian mixed GLM
Gaussian Imputation
new multivariate methods: factor analysis, MANOVA, repeated measures within ANOVA
GLM var_weights in addition to freq_weights
Holt-Winters and Exponential Smoothing

Log message:
Release 0.8.0

The main features of this release are several new time series models based on \ 
the statespace framework, multiple imputation using MICE as well as many other \ 
enhancements. The codebase also has been updated to be compatible with recent \ 
numpy and pandas releases.

Statsmodels is using now github to store the updated documentation which is \ 
available under http://www.statsmodels.org/stable for the last release, and \ 
http://www.statsmodels.org/dev/ for the development version.

Log message:
Import py-statsmodels-0.8.0rc1 as math/py-statsmodels.

Packaged for wip by Kamel Ibn Aziz Derouiche and myself.

Statsmodels is a Python package that provides a complement to scipy
for statistical computations including descriptive statistics and
estimation and inference for statistical models