[commons-statistics] 04/07: Remove PoissonDistribution normalApproximateProbability

[aherbert]

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

commit 234890b04dc5caf568af47ee59771ff809fe5085
Author: Alex Herbert <aherb...@apache.org>
AuthorDate: Tue Aug 3 00:01:18 2021 +0100

    Remove PoissonDistribution normalApproximateProbability
---
 .../statistics/distribution/PoissonDistribution.java | 20 --------------------
 .../distribution/PoissonDistributionTest.java        | 18 ------------------
 2 files changed, 38 deletions(-)

diff --git 
a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PoissonDistribution.java
 
b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PoissonDistribution.java
index bfcabed..7cfe1d0 100644
--- 
a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PoissonDistribution.java
+++ 
b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PoissonDistribution.java
@@ -30,8 +30,6 @@ public class PoissonDistribution extends 
AbstractDiscreteDistribution {
     private static final int DEFAULT_MAX_ITERATIONS = 10000000;
     /** Default convergence criterion. */
     private static final double DEFAULT_EPSILON = 1e-12;
-    /** Distribution used to compute normal approximation. */
-    private final NormalDistribution normal;
     /** Mean of the distribution. */
     private final double mean;
     /** Maximum number of iterations for cumulative probability. */
@@ -68,8 +66,6 @@ public class PoissonDistribution extends 
AbstractDiscreteDistribution {
         mean = p;
         this.epsilon = epsilon;
         this.maxIterations = maxIterations;
-
-        normal = new NormalDistribution(p, Math.sqrt(p));
     }
 
     /** {@inheritDoc} */
@@ -117,22 +113,6 @@ public class PoissonDistribution extends 
AbstractDiscreteDistribution {
                                         maxIterations);
     }
 
-    /**
-     * Calculates the Poisson distribution function using a normal
-     * approximation. The {@code N(mean, sqrt(mean))} distribution is used
-     * to approximate the Poisson distribution. The computation uses
-     * "half-correction" (evaluating the normal distribution function at
-     * {@code x + 0.5}).
-     *
-     * @param x Upper bound, inclusive.
-     * @return the distribution function value calculated using a normal
-     * approximation.
-     */
-    public double normalApproximateProbability(int x)  {
-        // Calculate the probability using half-correction.
-        return normal.cumulativeProbability(x + 0.5);
-    }
-
     /** {@inheritDoc} */
     @Override
     public double getMean() {
diff --git 
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PoissonDistributionTest.java
 
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PoissonDistributionTest.java
index dd95696..7257887 100644
--- 
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PoissonDistributionTest.java
+++ 
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PoissonDistributionTest.java
@@ -109,24 +109,6 @@ class PoissonDistributionTest extends 
DiscreteDistributionAbstractTest {
     //-------------------- Additional test cases 
-------------------------------
 
     /**
-     * Test the normal approximation of the Poisson distribution by
-     * calculating P(90 &le; X &le; 110) for X = Po(100) and
-     * P(9900 &le; X &le; 10200) for X  = Po(10000)
-     */
-    @Test
-    void testNormalApproximateProbability() {
-        PoissonDistribution dist = new PoissonDistribution(100);
-        double result = dist.normalApproximateProbability(110) -
-            dist.normalApproximateProbability(89);
-        Assertions.assertEquals(0.706281887248, result, 1e-10);
-
-        dist = new PoissonDistribution(10000);
-        result = dist.normalApproximateProbability(10200) -
-            dist.normalApproximateProbability(9899);
-        Assertions.assertEquals(0.820070051552, result, 1E-10);
-    }
-
-    /**
      * Test the degenerate cases of a 0.0 and 1.0 inverse cumulative 
probability.
      */
     @Test