updates to docs and such for release 0.3.1

CHANGELOG.md

@@ -1,3 +1,9 @@
+## Version 0.3.1
+
+This release is a quick fix for McNemar's test in the `contingency` module. There was some misleading literature in one 
+of the references which led to some incorrect changes in the previous release. This should be resolved now and an 
+update to the tests is coming up soon as well.
+
 ## Version 0.3.0
 
 ### New Additions:

docs/source/generated/hypothetical.gof.ChiSquareTest.rst

@@ -0,0 +1,22 @@
+hypothetical.gof.ChiSquareTest
+==============================
+
+.. currentmodule:: hypothetical.gof
+
+.. autoclass:: ChiSquareTest
+
+
+   .. automethod:: __init__
+
+
+   .. rubric:: Methods
+
+   .. autosummary::
+
+      ~ChiSquareTest.__init__
+
+
+
+
+
+

docs/source/generated/hypothetical.gof.JarqueBera.rst

@@ -0,0 +1,22 @@
+hypothetical.gof.JarqueBera
+===========================
+
+.. currentmodule:: hypothetical.gof
+
+.. autoclass:: JarqueBera
+
+
+   .. automethod:: __init__
+
+
+   .. rubric:: Methods
+
+   .. autosummary::
+
+      ~JarqueBera.__init__
+
+
+
+
+
+

docs/source/versions.rst

@@ -3,6 +3,69 @@
 Version History
 ===============
 
+Version 0.3.1
+-------------
+
+This release is a quick fix for McNemar's test in the `contingency` module. There was some misleading literature in one
+of the references which led to some incorrect changes in the previous release. This should be resolved now and an
+update to the tests is coming up soon as well.
+
+Version 0.3.0
+-------------
+
+New Additions:
+**************
+
+Factor Analysis
+
+* Factor Analysis
+    * Several algorithms for performing Factor Analysis are available, including principal components, principal
+      factors, and iterated principal factors.
+
+Nonparametric
+
+  * Wald-Wolfowitz Two Sample Nonparametric Runs Test
+    * A nonparametric test for determining if two independent samples have been drawn from the same population or that they differ in any respect.
+
+Analysis of Variance
+
+  * Tests for Homogenity of Variance
+    * Bartlett's Test for Homogenity of Variances
+    * Levene's Test for Homogenity of Variances
+  * Analysis of Variance
+    * Van Der Waerden's (normal scores) Test
+
+Critical Values
+
+  * Critical Value Tables and Lookup Functions
+  * D critical value (used in the Kolomogorov-Smirnov Goodness-of-Fit test) table and lookup function have been added.
+
+Updates and changes:
+********************
+
+Contingency
+
+  * Chi Square Test of Dependence
+    * Updates to methods in `ChiSquareContingency`.
+    * The previous measures of association method has been removed in favor of specific methods for each measure of association. These include:
+      * Cramer's $V$
+      * Phi Coefficient, $\phi$
+      * Contingency Coefficient, $C$
+      * Tschuprow's Coefficient, $T$ (new)
+      * The `test_summary` attribute of an initialized `ChiSquareContingency` class
+        now has separate key-value pairs for each computed association measure.
+  * McNemar's Test
+    * The test has been fixed to use the correct cells in the 2x2 contingency table.
+    * Continuity correction is now applied by default when performing the test. Setting the parameter `continuity=False`
+      will perform the non-continuity corrected version of the test.
+
+Nonparametric
+
+  * Median Test
+    * A multiple comparisons posthoc test is now available.
+
+* Many updates to documentation and docstrings.
+
 Version 0.2.0
 -------------
 

hypothetical/contingency.py

@@ -580,7 +580,7 @@ class McNemarTest(object):
 
     Examples
     --------
-    >>> m = McNemarTest([[59, 6], [16, 80]])
+    >>> m = McNemarTest([[59, 6], [16, 80]], continuity=False)
     >>> m.test_summary
     {'Asymptotic z-statistic': 2.1320071635561044,
      'Exact p-value': 0.052478790283203125,
@@ -589,7 +589,7 @@ class McNemarTest(object):
      'Mid p-value': 0.034689664840698256,
      'N': 161,
      'continuity': False}
-    >>> m2 = McNemarTest([[59, 6], [16, 80]], continuity=True)
+    >>> m2 = McNemarTest([[59, 6], [16, 80]])
     >>> m2.test_summary
     {'Asymptotic z-statistic': 1.9188064472004938,
      'Exact p-value': 0.052478790283203125,
@@ -611,8 +611,9 @@ class McNemarTest(object):
 
     Gibbons, J. D., & Chakraborti, S. (2010). Nonparametric statistical inference. London: Chapman & Hall.
 
-    Siegel, S. (1956). Nonparametric statistics: For the behavioral sciences.
-        McGraw-Hill. ISBN 07-057348-4
+    Wikipedia contributors. (2018, April 29). McNemar's test. In Wikipedia, The Free Encyclopedia.
+        Retrieved 12:24, August 15, 2018,
+        from https://en.wikipedia.org/w/index.php?title=McNemar%27s_test&oldid=838855782
 
     """
     def __init__(self, table, continuity=True):
@@ -668,9 +669,9 @@ def _mcnemar_test_stat(self):
 
         """
         if not self.continuity:
-            x2 = (self.table[0, 0] - self.table[1, 1]) ** 2 / (self.table[0, 1] + self.table[1, 0])
+            x2 = (self.table[0, 1] - self.table[1, 0]) ** 2 / (self.table[0, 1] + self.table[1, 0])
         else:
-            x2 = (np.absolute(self.table[0, 0] - self.table[1, 1]) - 1) ** 2 / (self.table[0, 0] + self.table[1, 1])
+            x2 = (np.absolute(self.table[0, 1] - self.table[1, 0]) - 1) ** 2 / (self.table[0, 1] + self.table[1, 0])
 
         return x2
 
@@ -703,9 +704,9 @@ def _asymptotic_test(self):
 
         """
         if not self.continuity:
-            z_asymptotic = (self.table[1, 0] - self.table[0, 1]) / np.sqrt(self.table[0, 1] + self.table[1, 0])
+            z_asymptotic = (self.table[0, 1] - self.table[1, 0]) / np.sqrt(self.table[0, 1] + self.table[1, 0])
         else:
-            z_asymptotic = (np.absolute(self.table[1, 0] - self.table[0, 1]) - 1) / \
+            z_asymptotic = (np.absolute(self.table[0, 1] - self.table[1, 0]) - 1) / \
                            np.sqrt(self.table[0, 1] + self.table[1, 0])
 
         return z_asymptotic

setup.py

@@ -4,7 +4,7 @@
 
 setup(
     name='hypothetical',
-    version='0.3.0',
+    version='0.3.1',
     author='Aaron Schlegel',
     author_email='aaron@aaronschlegel.me',
     description='Hypothesis testing and other testing methods',