MAINT: update setup.py and README.rst

README.rst

@@ -21,7 +21,7 @@ The documentation for the development version is at
 
 Recent improvements are highlighted in the release notes
 
-   http://www.statsmodels.org/stable/release/version0.8.html
+   http://www.statsmodels.org/stable/release/version0.9.html
 
 Backups of documentation are available at http://statsmodels.github.io/stable/
 and http://statsmodels.github.io/dev/.
@@ -38,17 +38,20 @@ Main Features
   - Weighted least squares
   - Least squares with autoregressive errors
   - Quantile regression
+  - Recursive least squares
 
 * Mixed Linear Model with mixed effects and variance components
 * GLM: Generalized linear models with support for all of the one-parameter
   exponential family distributions
+* Bayesian Mixed GLM for Binomial and Poisson
 * GEE: Generalized Estimating Equations for one-way clustered or longitudinal data
 * Discrete models:
 
   - Logit and Probit
   - Multinomial logit (MNLogit)
-  - Poisson regresion
+  - Poisson and Generalized Poisson regression
   - Negative Binomial regression
+  - Zero-Inflated Count models
 
 * RLM: Robust linear models with support for several M-estimators.
 * Time Series Analysis: models for time series analysis
@@ -58,10 +61,13 @@ Main Features
     - Seasonal ARIMA and ARIMAX models
     - VARMA and VARMAX models
     - Dynamic Factor models
+    - Unobserved Component models
 
   - Markov switching models (MSAR), also known as Hidden Markov Models (HMM)
   - Univariate time series analysis: AR, ARIMA
   - Vector autoregressive models, VAR and structural VAR
+  - Vector error correction modle, VECM
+  - exponential smoothing, Holt-Winters
   - Hypothesis tests for time series: unit root, cointegration and others
   - Descriptive statistics and process models for time series analysis
 
@@ -71,7 +77,14 @@ Main Features
   - Survivor function estimation (Kaplan-Meier)
   - Cumulative incidence function estimation
 
-* Nonparametric statistics: (Univariate) kernel density estimators
+* Multivariate:
+
+  - Principal Component Analysis with missing data
+  - Factor Analysis with rotation
+  - MANOVA
+  - Canonical Correlation
+
+* Nonparametric statistics: Univariate and multivariate kernel density estimators
 * Datasets: Datasets used for examples and in testing
 * Statistics: a wide range of statistical tests
 
@@ -80,12 +93,13 @@ Main Features
   - functions for multiple testing
   - various additional statistical tests
 
-* Imputation with MICE and regression on order statistic
+* Imputation with MICE, regression on order statistic and Gaussian imputation
 * Mediation analysis
-* Principal Component Analysis with missing data
+* Graphics includes plot functions for visual analysis of data and model results
+
 * I/O
 
-  - Tools for reading Stata .dta files into numpy arrays.
+  - Tools for reading Stata .dta files, but pandas has a more recent version
   - Table output to ascii, latex, and html
 
 * Miscellaneous models
@@ -117,9 +131,6 @@ Binaries can be installed in Anaconda
 
     conda install statsmodels
 
-Development snapshots are also available in Anaconda (infrequently updated)
-
-    conda install -c https://conda.binstar.org/statsmodels statsmodels
 
 Installing from sources
 =======================

docs/source/release/index.rst

@@ -16,6 +16,7 @@ What's new in Statsmodels
 .. toctree::
    :maxdepth: 1
 
+   version0.9
    version0.8
    version0.7
    version0.6

setup.py

@@ -56,7 +56,7 @@
 DISTNAME = 'statsmodels'
 DESCRIPTION = 'Statistical computations and models for Python'
 LONG_DESCRIPTION = README
-MAINTAINER = 'Skipper Seabold, Josef Perktold'
+MAINTAINER = 'Josef Perktold, Chad Fulton, Kerby Shedden'
 MAINTAINER_EMAIL ='pystatsmodels@googlegroups.com'
 URL = 'http://www.statsmodels.org/'
 LICENSE = 'BSD License'
@@ -177,6 +177,7 @@ def check_dependency_versions(min_versions):
                'Environment :: Console',
                'Programming Language :: Cython',
                'Programming Language :: Python :: 2.7',
+               'Programming Language :: Python :: 3.3',
                'Programming Language :: Python :: 3.4',
                'Programming Language :: Python :: 3.5',
                'Programming Language :: Python :: 3.6',
@@ -186,6 +187,7 @@ def check_dependency_versions(min_versions):
                'Intended Audience :: Science/Research',
                'Natural Language :: English',
                'License :: OSI Approved :: BSD License',
+               'Topic :: Office/Business :: Financial',
                'Topic :: Scientific/Engineering']
 
 # Return the git revision as a string
@@ -494,14 +496,11 @@ def get_data_files():
         os.unlink('MANIFEST')
 
     min_versions = {
-        'numpy' : '1.6.2',
-        'scipy' : '0.11',
-        'pandas' : '0.13',
-        'patsy' : '0.2.1',
+        'numpy' : '1.9',
+        'scipy' : '0.14',
+        'pandas' : '0.14',
+        'patsy' : '0.4.0',
                    }
-    if sys.version_info[0] == 3 and sys.version_info[1] >= 3:
-        # 3.3 needs numpy 1.7+
-        min_versions.update({"numpy" : "1.7.0"})
 
     (setup_requires,
      install_requires) = check_dependency_versions(min_versions)
@@ -543,13 +542,13 @@ def get_data_files():
     if not os.path.exists(os.path.join(cwd, 'PKG-INFO')) and not no_frills:
         # Generate Cython sources, unless building from source release
         generate_cython()
-    extras = {'docs': ['sphinx>=1.3.5',
-                       'nbconvert>=4.2.0',
+    extras = {'docs': ['sphinx',
+                       'nbconvert',
                        'jupyter_client',
                        'ipykernel',
                        'matplotlib',
-                       'nbformat>=4.0.1',
-                       'numpydoc>=0.6.0',
+                       'nbformat',
+                       'numpydoc',
                        'pandas-datareader']}
 
     setup(name = DISTNAME,