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new 02b3084 STATISTICS-67: Add inference module to the user guide
02b3084 is described below
commit 02b30848497ad9d6cecafc8843b9eb9eefdc1c8e
Author: aherbert <[email protected]>
AuthorDate: Mon Feb 20 13:52:16 2023 +0000
STATISTICS-67: Add inference module to the user guide
---
.../src/site/xdoc/index.xml | 2 +-
.../statistics/inference/UserGuideTest.java | 100 +++++++++++++++
src/site/site.xml | 1 +
src/site/xdoc/index.xml | 15 +++
src/site/xdoc/userguide/index.xml | 138 +++++++++++++++++++++
5 files changed, 255 insertions(+), 1 deletion(-)
diff --git a/commons-statistics-inference/src/site/xdoc/index.xml
b/commons-statistics-inference/src/site/xdoc/index.xml
index 78caeef..ab86ff4 100644
--- a/commons-statistics-inference/src/site/xdoc/index.xml
+++ b/commons-statistics-inference/src/site/xdoc/index.xml
@@ -43,7 +43,7 @@ double alpha = 1e-3;
// Fail if we can *reject* the null hypothesis with confidence (1 - alpha)
// that the observed match the expected
if (ChiSquareTest.withDefaults().test(expected, observed).reject(alpha)) {
- // Not significant ...
+ // Significant deviation from the expected ...
}
</source>
diff --git
a/commons-statistics-inference/src/test/java/org/apache/commons/statistics/inference/UserGuideTest.java
b/commons-statistics-inference/src/test/java/org/apache/commons/statistics/inference/UserGuideTest.java
new file mode 100644
index 0000000..e2e62b4
--- /dev/null
+++
b/commons-statistics-inference/src/test/java/org/apache/commons/statistics/inference/UserGuideTest.java
@@ -0,0 +1,100 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.commons.statistics.inference;
+
+import java.util.Arrays;
+import org.junit.jupiter.api.Assertions;
+import org.junit.jupiter.api.Test;
+
+/**
+ * Test code used in the inference section of the user guide.
+ */
+class UserGuideTest {
+ @Test
+ void testChiSquaredTest() {
+ double[] expected = {0.25, 0.5, 0.25};
+ long[] observed = {57, 123, 38};
+ SignificanceResult result = ChiSquareTest.withDefaults()
+ .test(expected, observed);
+ Assertions.assertEquals(0.0316148, result.getPValue(), 1e-4);
+ Assertions.assertTrue(result.reject(0.05));
+ Assertions.assertFalse(result.reject(0.01));
+ }
+
+ @Test
+ void testTTest() {
+ // Generated with:
+ // from scipy.stats import norm, ttest_rel
+ // x = norm(73, 10).rvs(10).astype(int)
+ // y = norm(66, 12).rvs(10).astype(int)
+ // ttest_rel(x, y, alternative='greater')
+ // (repeated until the test was just above the 0.05 significance level)
+ double[] math = {53, 69, 65, 65, 67, 79, 86, 65, 62, 69};
+ double[] science = {75, 65, 68, 63, 55, 65, 73, 45, 51, 52};
+ Assertions.assertEquals(68.0,
Arrays.stream(math).average().getAsDouble());
+ Assertions.assertEquals(61.2,
Arrays.stream(science).average().getAsDouble());
+ SignificanceResult result = TTest.withDefaults()
+
.with(AlternativeHypothesis.GREATER_THAN)
+ .pairedTest(math, science);
+ Assertions.assertEquals(0.05764, result.getPValue(), 1e-5);
+ Assertions.assertFalse(result.reject(0.05));
+ }
+
+ @Test
+ void testGTestIntrinsic() {
+ // See: http://www.biostathandbook.com/gtestgof.html
+
+ // Allele frequencies: Mpi 90/90, Mpi 90/100, Mpi 100/100
+ long[] observed = {1203, 2919, 1678};
+ // Mpi 90 proportion
+ double p = (2.0 * observed[0] + observed[1]) / (2 *
Arrays.stream(observed).sum());
+ Assertions.assertEquals(0.459, p, 1e-2);
+
+ // Hardy-Weinberg proportions
+ double[] expected = {p * p, 2 * p * (1 - p), (1 - p) * (1 - p)};
+ Assertions.assertArrayEquals(new double[] {0.211, 0.497, 0.293},
expected, 5e-3);
+
+ SignificanceResult result = GTest.withDefaults()
+ .withDegreesOfFreedomAdjustment(1)
+ .test(expected, observed);
+ Assertions.assertEquals(1.03, result.getStatistic(), 5e-2);
+ Assertions.assertEquals(0.309, result.getPValue(), 5e-3);
+ Assertions.assertFalse(result.reject(0.05));
+ }
+
+ @Test
+ void testAOV() {
+ // See: http://www.biostathandbook.com/onewayanova.html
+
+ double[] tillamook = {0.0571, 0.0813, 0.0831, 0.0976, 0.0817, 0.0859,
0.0735, 0.0659, 0.0923, 0.0836};
+ double[] newport = {0.0873, 0.0662, 0.0672, 0.0819, 0.0749, 0.0649,
0.0835, 0.0725};
+ double[] petersburg = {0.0974, 0.1352, 0.0817, 0.1016, 0.0968, 0.1064,
0.105};
+ double[] magadan = {0.1033, 0.0915, 0.0781, 0.0685, 0.0677, 0.0697,
0.0764, 0.0689};
+ double[] tvarminne = {0.0703, 0.1026, 0.0956, 0.0973, 0.1039, 0.1045};
+
+ OneWayAnova.Result result = OneWayAnova.withDefaults()
+ .test(Arrays.asList(tillamook,
newport, petersburg, magadan, tvarminne));
+ Assertions.assertEquals(4, result.getDFBG());
+ Assertions.assertEquals(34, result.getDFWG());
+ Assertions.assertEquals(0.001113, result.getMSBG(), 2e-5);
+ Assertions.assertEquals(0.000159, result.getMSWG(), 1e-5);
+ Assertions.assertEquals(7.12, result.getStatistic(), 1e-2);
+ Assertions.assertEquals(2.8e-4, result.getPValue(), 1e-5);
+ Assertions.assertTrue(result.reject(0.001));
+ }
+}
diff --git a/src/site/site.xml b/src/site/site.xml
index a528563..65e41c0 100644
--- a/src/site/site.xml
+++ b/src/site/site.xml
@@ -49,6 +49,7 @@
<item name="Overview" href="/userguide/index.html#overview"/>
<item name="Example Modules"
href="/userguide/index.html#example-modules"/>
<item name="Probability Distributions"
href="/userguide/index.html#distributions"/>
+ <item name="Inference" href="/userguide/index.html#inference"/>
<item name="Ranking" href="/userguide/index.html#ranking"/>
</menu>
</body>
diff --git a/src/site/xdoc/index.xml b/src/site/xdoc/index.xml
index 3850790..463e60f 100644
--- a/src/site/xdoc/index.xml
+++ b/src/site/xdoc/index.xml
@@ -42,6 +42,21 @@ double upperTail = t.survivalProbability(2.75); //
P(T(29) > 2.75)
PoissonDistribution p = PoissonDistribution.of(4.56);
int x = p.inverseCumulativeProbability(0.99);
+</source>
+
+ <p>
+ Hypothesis testing can be performed for various statistical tests, for
example:
+ </p>
+
+<source class="prettyprint">
+double[] math = {53, 69, 65, 65, 67, 79, 86, 65, 62, 69}; // mean = 68.0
+double[] science = {75, 65, 68, 63, 55, 65, 73, 45, 51, 52}; // mean = 61.2
+
+SignificanceResult result = TTest.withDefaults()
+ .with(AlternativeHypothesis.GREATER_THAN)
+ .pairedTest(math, science);
+result.getPValue(); // 0.05764
+result.reject(0.05); // false
</source>
<p>
diff --git a/src/site/xdoc/userguide/index.xml
b/src/site/xdoc/userguide/index.xml
index 4ddcee5..c187a15 100644
--- a/src/site/xdoc/userguide/index.xml
+++ b/src/site/xdoc/userguide/index.xml
@@ -55,6 +55,17 @@
</li>
</ul>
</li>
+ <li>
+ <a href="#inference">Inference</a>
+ <ul>
+ <li>
+ <a href="#inference_overview">Overview</a>
+ </li>
+ <li>
+ <a href="#inference_examples">Examples</a>
+ </li>
+ </ul>
+ </li>
<li>
<a href="#ranking">Ranking</a>
</li>
@@ -78,6 +89,14 @@
commons-statistics-distribution</a></code> - Provides interfaces
and classes for probability distributions.
</li>
+ <li>
+ <code><a href="../commons-statistics-inference/index.html">
+ commons-statistics-inference</a></code> - Provides hypothesis
testing.
+ </li>
+ <li>
+ <code><a href="../commons-statistics-ranking/index.html">
+ commons-statistics-ranking</a></code> - Provides rank
transformations.
+ </li>
</ul>
</section>
@@ -335,6 +354,125 @@ double x2 = chi2.inverseSurvivalProbability(q);
</p>
</subsection>
</section>
+ <section name="Inference" id="inference">
+ <p>
+ The <code>commons-statistics-inference</code> module provides
hypothesis testing.
+ </p>
+ <subsection name="Overview" id="inference_overview">
+ <p>
+ The module provides test classes that implement a single, or family,
of statistical
+ tests. Each test class provides methods to compute a test statistic
and a p-value for the
+ significance of the statistic. These can be computed together using
a <code>test</code>
+ method and returned as a
+ <a
href="../commons-statistics-inference/apidocs/org/apache/commons/statistics/inference/DiscreteDistribution.html">SignificanceResult</a>.
+ The <code>SignificanceResult</code> has a method that can be used to
<code>reject</code>
+ the null hypothesis at the provided significance level. Test classes
may extend the
+ <code>SignificanceResult</code> to return more information about the
test result,
+ for example the computed degrees of freedom.
+ </p>
+ <p>
+ Alternatively a <code>statistic</code> method is provided to compute
<i>only</i> the
+ statistic as a <code>double</code> value. This statistic can be
compared to a pre-computed
+ critical value, for example from a table of critical values.
+ </p>
+ <p>
+ A test is obtained using the <code>withDefaults()</code> method to
return the test with
+ all options set to their default value. Any test options can be
configured using
+ property change methods to return a new instance of the test. Tests
that support an
+ <a
href="../commons-statistics-inference/apidocs/org/apache/commons/statistics/inference/AlternativeHypothesis.html">
+ alternate hypothesis</a> will use a two-sided test by default. Test
that support multiple
+ <a
href="../commons-statistics-inference/apidocs/org/apache/commons/statistics/inference/PValueMethod.html">
+ p-value methods</a> will default to an appropriate computation for
the size of the input
+ data. Unless otherwise noted test instances are immutable.
+ </p>
+ </subsection>
+ <subsection name="Examples" id="inference_examples">
+ <p>
+ A chi-square test that the observed counts conform to the expected
frequencies.
+ </p>
+<source class="prettyprint">
+double[] expected = {0.25, 0.5, 0.25};
+long[] observed = {57, 123, 38};
+
+SignificanceResult result = ChiSquareTest.withDefaults()
+ .test(expected, observed);
+result.getPValue(); // 0.0316148
+result.reject(0.05); // true
+result.reject(0.01); // false
+</source>
+ <p>
+ A paired t-test that the student's marks in the math exam were
greater than the science
+ exam. This fails to reject the null hypothesis (that there was no
difference) with
+ 95% confidence.
+ </p>
+<source class="prettyprint">
+double[] math = {53, 69, 65, 65, 67, 79, 86, 65, 62, 69}; // mean = 68.0
+double[] science = {75, 65, 68, 63, 55, 65, 73, 45, 51, 52}; // mean = 61.2
+
+SignificanceResult result = TTest.withDefaults()
+ .with(AlternativeHypothesis.GREATER_THAN)
+ .pairedTest(math, science);
+result.getPValue(); // 0.05764
+result.reject(0.05); // false
+</source>
+ <p>
+ A G-test that the allele frequencies conform to the expected
Hardy-Weinberg proportions.
+ This is an example of an intrinsic hypothesis where the expected
frequencies are computed
+ using the observations and the degrees of freedom must be adjusted.
+ The data is from McDonald (1989) Selection component analysis
+ of the Mpi locus in the amphipod Platorchestia platensis.
+ <i>Heredity</i> <b>62</b>: 243-249.
+ </p>
+<source class="prettyprint">
+// Allele frequencies: Mpi 90/90, Mpi 90/100, Mpi 100/100
+long[] observed = {1203, 2919, 1678};
+// Mpi 90 proportion
+double p = (2.0 * observed[0] + observed[1]) /
+ (2 * Arrays.stream(observed).sum()); // 5325 / 11600 = 0.459
+
+// Hardy-Weinberg proportions
+double[] expected = {p * p, 2 * p * (1 - p), (1 - p) * (1 - p)};
+// 0.211, 0.497, 0.293
+
+SignificanceResult result = GTest.withDefaults()
+ .withDegreesOfFreedomAdjustment(1)
+ .test(expected, observed);
+result.getStatistic(); // 1.03
+result.getPValue(); // 0.309
+result.reject(0.05); // false
+</source>
+ <p>
+ A one-way analysis of variance test. This is an example where the
result has more
+ information than the test statistic and the p-value.
+ The data is from McDonald <i>et al</i> (1991) Allozymes and
morphometric characters of
+ three species of Mytilus in the Northern and Southern Hemispheres.
+ <i>Marine Biology</i> <b>111</b>: 323-333.
+ </p>
+<source class="prettyprint">
+double[] tillamook = {0.0571, 0.0813, 0.0831, 0.0976, 0.0817, 0.0859, 0.0735,
0.0659, 0.0923, 0.0836};
+double[] newport = {0.0873, 0.0662, 0.0672, 0.0819, 0.0749, 0.0649, 0.0835,
0.0725};
+double[] petersburg = {0.0974, 0.1352, 0.0817, 0.1016, 0.0968, 0.1064, 0.105};
+double[] magadan = {0.1033, 0.0915, 0.0781, 0.0685, 0.0677, 0.0697, 0.0764,
0.0689};
+double[] tvarminne = {0.0703, 0.1026, 0.0956, 0.0973, 0.1039, 0.1045};
+
+Collection<double[]> data = Arrays.asList(tillamook, newport,
petersburg, magadan, tvarminne);
+OneWayAnova.Result result = OneWayAnova.withDefaults()
+ .test(data);
+result.getStatistic(); // 7.12
+result.getPValue(); // 2.8e-4
+result.reject(0.001); // true
+</source>
+ <p>
+ The result also provides the between and within group degrees of
freedom and the mean
+ squares allowing reporting of the results in a table:
+ </p>
+ <table>
+ <tr><th></th><th>degrees of freedom</th><th>mean
square</th><th>F</th><th>p</th></tr>
+ <tr><td>between
groups</td><td>4</td><td>0.001113</td><td>7.12</td><td>2.8e-4</td></tr>
+ <tr><td>within
groups</td><td>34</td><td>0.000159</td><td></td><td></td></tr>
+ </table>
+ </subsection>
+ </section>
<section name="Ranking" id="ranking">
<p>
The <code>commons-statistics-ranking</code> module provides rank
transformations.
