[commons-statistics] 09/11: Add NakagamiDistribution testMoments.

[ah...@apache.org]

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aherbert pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-statistics.git

commit af7ad85bcc9a480594bd89df569486f7ded8538a
Author: aherbert <ah...@apache.org>
AuthorDate: Wed Jun 24 13:32:29 2020 +0100

    Add NakagamiDistribution testMoments.
---
 .../distribution/NakagamiDistributionTest.java         | 18 ++++++++++++++----
 1 file changed, 14 insertions(+), 4 deletions(-)

diff --git a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/NakagamiDistributionTest.java b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/NakagamiDistributionTest.java
index 3ed68fd..9c450e2 100644
--- a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/NakagamiDistributionTest.java
+++ b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/NakagamiDistributionTest.java
@@ -17,7 +17,6 @@
 package org.apache.commons.statistics.distribution;
 
 import org.junit.jupiter.api.Assertions;
-import org.junit.jupiter.api.Disabled;
 import org.junit.jupiter.api.Test;
 
 /**
@@ -75,10 +74,21 @@ public class NakagamiDistributionTest extends ContinuousDistributionAbstractTest
     }
 
     @Test
-    @Disabled
     public void testMoments() {
-        // TODO.
-        // Currently the mean and variance are only used when solving the inverse cumulative probability.
+        // Values obtained using Matlab, e.g.
+        // format long;
+        // pd = makedist('Nakagami','mu',0.5,'omega',1.0);
+        // disp([pd.mean, pd.var])
+        NakagamiDistribution dist;
+        final double eps = 1e-9;
+
+        dist = new NakagamiDistribution(0.5, 1.0);
+        Assertions.assertEquals(0.797884560802866, dist.getMean(), eps);
+        Assertions.assertEquals(0.363380227632418, dist.getVariance(), eps);
+
+        dist = new NakagamiDistribution(1.23, 2.5);
+        Assertions.assertEquals(1.431786259006201, dist.getMean(), eps);
+        Assertions.assertEquals(0.449988108521028, dist.getVariance(), eps);
     }
 
     @Test