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117 lines
3.6 KiB
Plaintext
117 lines
3.6 KiB
Plaintext
Release History
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===============
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trunk for 0.4.0
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---------------
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* tools.tools.ECDF -> distributions.ECDF
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* tools.tools.monotone_fn_inverter -> distributions.monotone_fn_inverter
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* tools.tools.StepFunction -> distributions.StepFunction
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0.3.1
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-----
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* Removed academic-only WFS dataset.
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* Fix easy_install issue on Windows.
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0.3.0
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-----
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*Changes that break backwards compatibility*
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Added api.py for importing. So the new convention for importing is::
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import scikits.statsmodels.api as sm
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Importing from modules directly now avoids unnecessary imports and increases
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the import speed if a library or user only needs specific functions.
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* sandbox/output.py -> iolib/table.py
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* lib/io.py -> iolib/foreign.py (Now contains Stata .dta format reader)
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* family -> families
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* families.links.inverse -> families.links.inverse_power
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* Datasets' Load class is now load function.
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* regression.py -> regression/linear_model.py
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* discretemod.py -> discrete/discrete_model.py
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* rlm.py -> robust/robust_linear_model.py
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* glm.py -> genmod/generalized_linear_model.py
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* model.py -> base/model.py
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* t() method -> tvalues attribute (t() still exists but raises a warning)
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*Main changes and additions*
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* Numerous bugfixes.
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* Time Series Analysis model (tsa)
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- Vector Autoregression Models VAR (tsa.VAR)
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- Autogressive Models AR (tsa.AR)
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- Autoregressive Moving Average Models ARMA (tsa.ARMA)
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optionally uses Cython for Kalman Filtering
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use setup.py install with option --with-cython
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- Baxter-King band-pass filter (tsa.filters.bkfilter)
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- Hodrick-Prescott filter (tsa.filters.hpfilter)
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- Christiano-Fitzgerald filter (tsa.filters.cffilter)
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* Improved maximum likelihood framework uses all available scipy.optimize solvers
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* Refactor of the datasets sub-package.
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* Added more datasets for examples.
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* Removed RPy dependency for running the test suite.
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* Refactored the test suite.
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* Refactored codebase/directory structure.
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* Support for offset and exposure in GLM.
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* Removed data_weights argument to GLM.fit for Binomial models.
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* New statistical tests, especially diagnostic and specification tests
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* Multiple test correction
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* General Method of Moment framework in sandbox
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* Improved documentation
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* and other additions
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0.2.0
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-----
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*Main changes*
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* renames for more consistency
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RLM.fitted_values -> RLM.fittedvalues
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GLMResults.resid_dev -> GLMResults.resid_deviance
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* GLMResults, RegressionResults:
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lazy calculations, convert attributes to properties with _cache
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* fix tests to run without rpy
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* expanded examples in examples directory
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* add PyDTA to lib.io -- functions for reading Stata .dta binary files
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and converting
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them to numpy arrays
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* made tools.categorical much more robust
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* add_constant now takes a prepend argument
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* fix GLS to work with only a one column design
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*New*
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* add four new datasets
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- A dataset from the American National Election Studies (1996)
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- Grunfeld (1950) investment data
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- Spector and Mazzeo (1980) program effectiveness data
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- A US macroeconomic dataset
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* add four new Maximum Likelihood Estimators for models with a discrete
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dependent variables with examples
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- Logit
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- Probit
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- MNLogit (multinomial logit)
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- Poisson
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*Sandbox*
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* add qqplot in sandbox.graphics
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* add sandbox.tsa (time series analysis) and sandbox.regression (anova)
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* add principal component analysis in sandbox.tools
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* add Seemingly Unrelated Regression (SUR) and Two-Stage Least Squares
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for systems of equations in sandbox.sysreg.Sem2SLS
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* add restricted least squares (RLS)
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0.1.0b1
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-------
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* initial release
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