Merge pull request statsmodels#5990 from bashtage/spelling

MAINT/DOC: Add spell checking

Author: bashtage

README.rst

@@ -104,7 +104,7 @@ Main Features
 
 * Miscellaneous models
 * Sandbox: statsmodels contains a sandbox folder with code in various stages of
-  developement and testing which is not considered "production ready".  This covers
+  development and testing which is not considered "production ready".  This covers
   among others
 
   - Generalized method of moments (GMM) estimators

docs/source/conf.py

@@ -54,6 +54,16 @@
               'numpydoc'
               ]
 
+try:
+    import sphinxcontrib.spelling  # noqa: F401
+except ImportError as err:  # noqa: F841
+    pass
+else:
+    extensions.append('sphinxcontrib.spelling')
+
+spelling_word_list_filename = ['spelling_wordlist.txt', 'names_wordlist.txt']
+spelling_ignore_pypi_package_names = True
+
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['_templates']
 

docs/source/datasets/dataset_proposal.rst

@@ -2,7 +2,7 @@
 
 .. _dataset_proposal:
 
-Dataset for statmodels: design proposal
+Dataset for statsmodels: design proposal
 ===============================================
 
 One of the thing numpy/scipy is missing now is a set of datasets, available for

docs/source/dev/test_notes.rst

@@ -12,7 +12,7 @@ using a development install of statsmodels::
     python setup.py develop
 
 This will compile the C code and add statsmodels to your activate python
-environment by creating links from your python environemnt's libraries
+environment by creating links from your python environment's libraries
 to the statsmodels source code. Therefore, changes to pure python code will
 be immediately available to the user without a re-install.
 

docs/source/names_wordlist.txt

@@ -0,0 +1,91 @@
+Josef
+Helmert
+Akaike
+Anscombe
+Armitage
+Athanasopoulos
+Augspurger
+Azzalini
+Bai
+Benjamini
+Bera
+Berndt
+Breslow
+Breusch
+Brockwell
+Bronwyn
+Broyden
+Charlier
+Denton
+Doornik
+Driscoll
+Durbin
+Econometrica
+Efron
+El
+Engle
+Fleiss
+Goldfarb
+Goldfeld
+Gommers
+Granger
+Hampel
+Hannan
+Hastie
+Hauck
+Hausman
+Helmert
+Helmut
+Hobson
+Hochberg
+Hodrick
+Kaplan
+Hurvich
+Hyndman
+Jarque
+Johansen
+Jurgen
+Kerby
+Kolmogorov
+Koopman
+Kraay
+Kwiatkowski
+Levinson
+Liang
+Liu
+Ljung
+Lütkepohl
+Nelder
+Newey
+Nino
+Penrose
+Perktold
+Ploberger
+Quackenbush
+Raphson
+Ridout
+Satterthwait
+Schwarz
+Schwert
+Seabold
+Shephard
+Shanno
+Shedden
+Sidak
+Siem
+Silverman
+Smirnov
+Springer
+Stata
+Tibshirani
+Tukey
+Yichuan
+Zeger
+Zha
+Reuille
+Kotz
+Grunfeld
+Longley
+Koenker
+gliptak
+Spector

docs/source/plots/graphics_regression_abline.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 '''
-Using the state crime dataset seperately plot the effect of the each
+Using the state crime dataset separately plot the effect of the each
 variable on the on the outcome, murder rate while accounting for the effect
 of all other variables in the model.
 

docs/source/plots/graphics_regression_ccpr_grid.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 '''
-Using the state crime dataset seperately plot the effect of the each
+Using the state crime dataset separately plot the effect of the each
 variable on the on the outcome, murder rate while accounting for the effect
 of all other variables in the model.
 

docs/source/plots/graphics_regression_partregress_grid.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 '''
-Using the state crime dataset seperately plot the effect of the each
+Using the state crime dataset separately plot the effect of the each
 variable on the on the outcome, murder rate while accounting for the effect
 of all other variables in the model visualized with a grid of partial
 regression plots.

docs/source/release/index.rst

@@ -23,4 +23,4 @@ What's new in Statsmodels
    version0.6
    version0.5
 
-For an overview of changes that occured previous to the 0.5.0 release see :ref:`old_changes`.
+For an overview of changes that occurred previous to the 0.5.0 release see :ref:`old_changes`.

docs/source/release/old_changes.rst

@@ -170,7 +170,7 @@ the import speed if a library or user only needs specific functions.
 * Time Series Analysis model (tsa)
 
   - Vector Autoregression Models VAR (tsa.VAR)
-  - Autogressive Models AR (tsa.AR)
+  - Autoregressive 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

docs/source/release/version0.10.rst

@@ -663,7 +663,7 @@ Thie following Pull Requests were merged since the last release:
 * :pr:`5275`: ENH/BUG Modify GEE indexing to remove numpy warnings
 * :pr:`5277`: DOC: Clarify/fix docs on GLM scale estimation for negative binomial
 * :pr:`5292`: DOC: Remove only_directive
-* :pr:`5295`: TST: Added random seed to test_gee and verifed working
+* :pr:`5295`: TST: Added random seed to test_gee and verified working
 * :pr:`5300`: DOC fix docstring in stattools.py
 * :pr:`5301`: BUG: MICEData sets initial imputation incorrectly
 * :pr:`5304`: ENH: conditional logistic and Poisson regression

docs/source/release/version0.5.rst

@@ -100,7 +100,7 @@ New and Improved Graphics
 Power and Sample Size Calculations
 ----------------------------------
 
-The power module (``statsmodel.stats.power``) currently implements power and sample size calculations for the t-tests (:class:`sm.stats.TTestPower <TTestPower>`, :class:`sm.stats.TTestIndPower <TTestIndPower>`), normal based test (:class:`sm.stats.NormIndPower <NormIndPower>`), F-tests (:class:`sm.stats.FTestPower <FTestPower>`, `:class:sm.stats.FTestAnovaPower <FTestAnovaPower>`) and Chisquare goodness of fit (:class:`sm.stats.GofChisquarePower <GofChisquarePower>`) test. The implementation is class based, but the module also provides three shortcut functions, :func:`sm.stats.tt_solve_power <tt_solve_power>`, :func:`sm.stats.tt_ind_solve_power <tt_ind_solve_power>` and :func:`sm.stats.zt_ind_solve_power <zt_ind_solve_power>` to solve for any one of the parameters of the power equations. See this `blog post <http://jpktd.blogspot.fr/2013/03/statistical-power-in-statsmodels.html>`_ for a more in-depth description of the additions.
+The power module (``statsmodels.stats.power``) currently implements power and sample size calculations for the t-tests (:class:`sm.stats.TTestPower <TTestPower>`, :class:`sm.stats.TTestIndPower <TTestIndPower>`), normal based test (:class:`sm.stats.NormIndPower <NormIndPower>`), F-tests (:class:`sm.stats.FTestPower <FTestPower>`, `:class:sm.stats.FTestAnovaPower <FTestAnovaPower>`) and Chisquare goodness of fit (:class:`sm.stats.GofChisquarePower <GofChisquarePower>`) test. The implementation is class based, but the module also provides three shortcut functions, :func:`sm.stats.tt_solve_power <tt_solve_power>`, :func:`sm.stats.tt_ind_solve_power <tt_ind_solve_power>` and :func:`sm.stats.zt_ind_solve_power <zt_ind_solve_power>` to solve for any one of the parameters of the power equations. See this `blog post <http://jpktd.blogspot.fr/2013/03/statistical-power-in-statsmodels.html>`_ for a more in-depth description of the additions.
 
 
 Other important new features
@@ -251,7 +251,7 @@ Pull Requests (172):
 * :ghpull:`1009`: MAINT: Add .mailmap file.
 * :ghpull:`817`: Add 3 new unit tests for arima_process
 * :ghpull:`1001`: BUG include_package_data for install closes #907
-* :ghpull:`1005`: GITHUB: Contributing guidlines
+* :ghpull:`1005`: GITHUB: Contributing guidelines
 * :ghpull:`1007`: Cleanup docs for release
 * :ghpull:`1003`: BUG: Workaround for bug in sphinx 1.1.3. See #1002.
 * :ghpull:`1004`: DOC: Update maintainer notes with branching instructions.
@@ -277,7 +277,7 @@ Pull Requests (172):
 * :ghpull:`949`: BUG fix lowess sort when nans closes #946
 * :ghpull:`932`: ENH: support basinhopping solver in LikelihoodModel.fit()
 * :ghpull:`927`: DOC: clearer minimal example
-* :ghpull:`919`: Ols summary crash
+* :ghpull:`919`: OLS summary crash
 * :ghpull:`918`: Fixes10 emplike lowess
 * :ghpull:`909`: Bugs in GLM pvalues, more tests, pylint
 * :ghpull:`906`: ENH: No fmax with Windows SDK so define inline.
@@ -526,7 +526,7 @@ Issues (208):
 * :ghissue:`549`: Ship released patsy source in statsmodels
 * :ghissue:`588`: patsy is a hard dependency?
 * :ghissue:`716`: Tests missing for functions if pandas is used
-* :ghissue:`715`: statmodels regression plots not working with pandas datatypes
+* :ghissue:`715`: statsmodels regression plots not working with pandas datatypes
 * :ghissue:`450`: BUG: full_output in optimizers Likelihood model
 * :ghissue:`709`: DOCstrings linear models don't have missing params
 * :ghissue:`370`: BUG weightstats has wrong cov
@@ -593,7 +593,7 @@ Issues (208):
 * :ghissue:`495`: ENH: add footer SimpleTable
 * :ghissue:`402`: model._data -> model.data?
 * :ghissue:`477`: VAR NaN Bug
-* :ghissue:`421`: Enhancment: Handle Missing Data
+* :ghissue:`421`: Enhancement: Handle Missing Data
 * :ghissue:`489`: Expose model._data as model.data
 * :ghissue:`315`: tsa models assume pandas object indices are dates
 * :ghissue:`440`: arima predict is broken for steps > q and q != 1

docs/source/release/version0.6.rst

@@ -664,7 +664,7 @@ Issues (252):
 * :ghissue:`1730`: ENH/Bug cov_params, generalize, avoid ValueError
 * :ghissue:`1754`: BUG/REF: assignment to slices in numpy >= 1.9 (emplike)
 * :ghissue:`1409`: GEE test errors on Debian Wheezy
-* :ghissue:`1521`: ubuntu failues: tsa_plot and grouputils
+* :ghissue:`1521`: ubuntu failures: tsa_plot and grouputils
 * :ghissue:`1415`: test failure test_arima.test_small_data
 * :ghissue:`1213`: df_diff in anova_lm
 * :ghissue:`1323`: Contrast Results after t_test summary broken for 1 parameter
@@ -691,7 +691,7 @@ Issues (252):
 * :ghissue:`1067`: Kalman Filter convergence. How close is close enough?
 * :ghissue:`1281`: Newton convergence failure prints warnings instead of warning
 * :ghissue:`1628`: Unable to install statsmodels in the same requirements file as numpy, pandas, etc.
-* :ghissue:`617`: Problem in installing statsmodel in Fedora 17 64-bit
+* :ghissue:`617`: Problem in installing statsmodels in Fedora 17 64-bit
 * :ghissue:`935`: ll_null in likelihoodmodels discrete
 * :ghissue:`704`: datasets.sunspot: wrong link in description
 * :ghissue:`1222`: NegativeBinomial ignores exposure