scikits.statsmodels 0.3.1 (beta)

Statistical computations and models for use with SciPy

0.3.1

• Removed academic-only WFS dataset.
• Fix easy_install issue on Windows.

0.3.0

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.

• sandbox/output.py -> iolib/table.py
• 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.
• regression.py -> regression/linear_model.py
• discretemod.py -> discrete/discrete_model.py
• 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 and additions

• Numerous bugfixes.

• Time Series Analysis model (tsa) - Vector Autoregression Models VAR (tsa.VAR) - Autogressive Models AR (tsa.AR) - Autoregressive Moving Average Models ARMA (tsa.ARMA) :

  System Message: ERROR/3 (<string>, line 164)

  Unexpected indentation.

  optionally uses Cython for Kalman Filtering use setup.py install with option --with-cython

  System Message: WARNING/2 (<string>, line 166)

  Block quote ends without a blank line; unexpected unindent.

  • Baxter-King band-pass filter (tsa.filters.bkfilter)
  • Hodrick-Prescott filter (tsa.filters.hpfilter)
  • Christiano-Fitzgerald filter (tsa.filters.cffilter)

• Improved maximum likelihood framework uses all available scipy.optimize solvers

• Refactor of the datasets sub-package.

• Added more datasets for examples.

• Removed RPy dependency for running the test suite.

• Refactored the test suite.

• Refactored codebase/directory structure.

• Support for offset and exposure in GLM.

• Removed data_weights argument to GLM.fit for Binomial models.

• New statistical tests, especially diagnostic and specification tests

• Multiple test correction

• General Method of Moment framework in sandbox

• Improved documentation

• and other additions

0.2.0

main changes

• renames for more consistency RLM.fitted_values -> RLM.fittedvalues GLMResults.resid_dev -> GLMResults.resid_deviance

• GLMResults, RegressionResults: lazy calculations, convert attributes to properties with _cache

• fix tests to run without rpy

• expanded examples in examples directory

• add PyDTA to lib.io -- functions for reading Stata *.dta binary files and converting them to numpy arrays

  System Message: WARNING/2 (<string>, line 197); backlink

  Inline emphasis start-string without end-string.

• made tools.categorical much more robust

• add_constant now takes a prepend argument

• fix GLS to work with only a one column design

new

• add four new datasets

  • A dataset from the American National Election Studies (1996)
  • Grunfeld (1950) investment data
  • Spector and Mazzeo (1980) program effectiveness data
  • A US macroeconomic dataset

• add four new Maximum Likelihood Estimators for models with a discrete dependent variables with examples

  System Message: ERROR/3 (<string>, line 213)

  Unexpected indentation.

  • Logit
  • Probit
  • MNLogit (multinomial logit)
  • Poisson

sandbox

• add qqplot in sandbox.graphics
• add sandbox.tsa (time series analysis) and sandbox.regression (anova)
• add principal component analysis in sandbox.tools
• add Seemingly Unrelated Regression (SUR) and Two-Stage Least Squares for systems of equations in sandbox.sysreg.Sem2SLS
• add restricted least squares (RLS)

0.1.0b1

• initial release