more smaller fixes

   (import in api.py doesn't translate correctly with 2to3, results removed in linear_model)
setup.py update description from CHANGES.txt

CHANGES.txt

@@ -7,6 +7,9 @@ Added api.py for importing. So the new convention for importing is ::
 
 import scikits.statsmodels.api as sm
 
+Importing from modules directly now avoids unnecessary imports and increases
+the import speed if a library or user only needs specific functions.
+
 * sandbox/output.py -> iolib/table.py
 * lib/io.py -> iolib/foreign.py (Now contains Stata .dta format reader)
 * family -> families
@@ -17,7 +20,7 @@ import scikits.statsmodels.api as sm
 * rlm.py -> robust/robust_linear_model.py
 * glm.py -> genmod/generalized_linear_model.py
 * model.py -> base/model.py
-* t() method -> tvalues attribute
+* t() method -> tvalues attribute (t() still exists but raises a warning)
 
 *main changes and additions*
 

scikits/statsmodels/api.py

@@ -7,15 +7,17 @@
 import robust
 from .robust.robust_linear_model import RLM
 from .discrete.discrete_model import Poisson, Logit, Probit, MNLogit
-import tsa.api
-tsa = tsa.api
+from .tsa import api as tsa
+#import tsa.api
+#tsa = tsa.api
 from __init__ import test
 from version import __version__
 from info import __doc__
 
 import os
 
-chmpath = os.path.join(os.path.dirname(__file__),'docs\\build\\htmlhelp\\statsmodelsdoc.chm')
+chmpath = os.path.join(os.path.dirname(__file__),
+                       'docs\\build\\htmlhelp\\statsmodelsdoc.chm')
 if os.path.exists(chmpath):
     def open_help(chmpath=chmpath):
         from subprocess import Popen

scikits/statsmodels/examples/example_glsar.py

@@ -79,6 +79,7 @@
 
     for i in range(5):
         mod1.iterative_fit(1)
+        mod1.fit()
         print mod1.rho
         print mod1.results.params
 

scikits/statsmodels/sandbox/stats/stats_dhuard.py

@@ -146,7 +146,8 @@ def empiricalcdf(data, method='Hazen'):
     elif method == 'gringorten':
         cdf = (i-.44)/(N+.12)
     else:
-        raise 'Unknown method. Choose among Weibull, Hazen, Chegodayev, Cunnane, Gringorten and California.'
+        raise ValueError('Unknown method. Choose among Weibull, Hazen,'
+                         'Chegodayev, Cunnane, Gringorten and California.')
 
     return cdf
 
@@ -208,7 +209,8 @@ def empiricalcdf(self, data=None, method='Hazen'):
         elif method == 'gringorten':
             cdf = (i-.44)/(N+.12)
         else:
-            raise 'Unknown method. Choose among Weibull, Hazen, Chegodayev, Cunnane, Gringorten and California.'
+            raise ValueError('Unknown method. Choose among Weibull, Hazen,'
+                             'Chegodayev, Cunnane, Gringorten and California.')
 
         return cdf
 

setup.py

@@ -15,7 +15,7 @@
 linear models, and regression with discrete dependent variables, Logit,
 Probit, MNLogit, Poisson, based on maximum likelihood estimators,
 timeseries models, ARMA, AR and VAR. An extensive list of result statistics
-are avalable for each estimation problem. Statsmodels also contains
+are available for each estimation problem. Statsmodels also contains
 descriptive statistics, a wide range of statistical tests and more.
 
 We welcome feedback:
@@ -24,16 +24,22 @@
 
 For updated versions between releases, we recommend our repository at
 `<http://code.launchpad.net/statsmodels>`_ We will move to github in the
-near future.
+near future `<https://github.com/statsmodels>`_
 
 Main changes for 0.3.0
 ----------------------
 
-*Changes that break backwards compatability*
+*Changes that break backwards compatibility*
+
+Added api.py for importing. So the new convention for importing is ::
+
+import scikits.statsmodels.api as sm
+
+Importing from modules directly now avoids unnecessary imports and increases
+the import speed if a library or user only needs specific functions.
 
-* main import path is now scikits.statsmodels.api
 * sandbox/output.py -> iolib/table.py
-* lib/io.py -> iolib/foreign.py (stata data format reader available from iolib)
+* lib/io.py -> iolib/foreign.py (Now contains Stata .dta format reader)
 * family -> families
 * families.links.inverse -> families.links.inverse_power
 * Datasets' Load class is now load function.
@@ -42,16 +48,20 @@
 * rlm.py -> robust/robust_linear_model.py
 * glm.py -> genmod/generalized_linear_model.py
 * model.py -> base/model.py
+* t() method -> tvalues attribute (t() still exists but raises a warning)
 
-*main changes*
+*main changes and additions*
 
 * Numerous bugfixes.
 * Time Series Analysis model (tsa)
-* VAR (tsa.VAR)
-* ARMA models for time series. (tsa.AR)
-  -optionally uses Cython for Kalman Filtering
-* Improved maximum likelihood framework.
+  - Vector Autoregression Models VAR (tsa.VAR)
+  - Autogressive Models AR (tsa.AR)
+  - Autoregressive Moving Average Models ARMA (tsa.ARMA) :
+      optionally uses Cython for Kalman Filtering
+      use setup.py install with option --with-cython
+* Improved maximum likelihood framework uses all available scipy.optimize solvers
 * Refactor of the datasets sub-package.
+* Added Nile River dataset.
 * Removed RPy dependency for running the test suite.
 * Refactored the test suite.
 * Refactored codebase/directory structure.
@@ -60,8 +70,10 @@
 * New statistical tests, especially diagnostic and specification tests
 * Multiple test correction
 * General Method of Moment framework in sandbox
+* Improved documentation
 * and other additions
 
+
 Main Changes in 0.2.0
 ---------------------