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Posted to commits@commons.apache.org by ah...@apache.org on 2022/11/12 16:52:32 UTC

[commons-statistics] branch master updated (3dc9499 -> 956fe82)

This is an automated email from the ASF dual-hosted git repository.

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


    from 3dc9499  Test comments
     new 3ee52f7  Statistics-25: Remove T-dist switch to normal CDF
     new 956fe82  Triangular distribution documentation update

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repository and will be described in separate emails.  The revisions
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Summary of changes:
 .../statistics/distribution/TDistribution.java     | 10 -------
 .../distribution/TriangularDistribution.java       | 31 +++-------------------
 2 files changed, 4 insertions(+), 37 deletions(-)


[commons-statistics] 02/02: Triangular distribution documentation update

Posted by ah...@apache.org.
This is an automated email from the ASF dual-hosted git repository.

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

commit 956fe8291be392d0bcd67f7bbef40fda0a67cc19
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Sat Nov 12 16:51:42 2022 +0000

    Triangular distribution documentation update
    
    Switch mean/var function documentation to MathJax.
    
    Remove duplication of PDF definition.
    
    Remove CDF definition.
---
 .../distribution/TriangularDistribution.java       | 31 +++-------------------
 1 file changed, 4 insertions(+), 27 deletions(-)

diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TriangularDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TriangularDistribution.java
index aa45825..4f65543 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TriangularDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TriangularDistribution.java
@@ -104,18 +104,7 @@ public final class TriangularDistribution extends AbstractContinuousDistribution
         return c;
     }
 
-    /**
-     * {@inheritDoc}
-     *
-     * <p>For lower limit {@code a}, upper limit {@code b} and mode {@code c}, the
-     * PDF is given by
-     * <ul>
-     * <li>{@code 2 * (x - a) / [(b - a) * (c - a)]} if {@code a <= x < c},</li>
-     * <li>{@code 2 / (b - a)} if {@code x = c},</li>
-     * <li>{@code 2 * (b - x) / [(b - a) * (b - c)]} if {@code c < x <= b},</li>
-     * <li>{@code 0} otherwise.
-     * </ul>
-     */
+    /** {@inheritDoc} */
     @Override
     public double density(double x) {
         if (x < a) {
@@ -135,19 +124,7 @@ public final class TriangularDistribution extends AbstractContinuousDistribution
         return 0;
     }
 
-    /**
-     * {@inheritDoc}
-     *
-     * <p>For lower limit {@code a}, upper limit {@code b} and mode {@code c}, the
-     * CDF is given by
-     * <ul>
-     * <li>{@code 0} if {@code x < a},</li>
-     * <li>{@code (x - a)^2 / [(b - a) * (c - a)]} if {@code a <= x < c},</li>
-     * <li>{@code (c - a) / (b - a)} if {@code x = c},</li>
-     * <li>{@code 1 - (b - x)^2 / [(b - a) * (b - c)]} if {@code c < x <= b},</li>
-     * <li>{@code 1} if {@code x > b}.</li>
-     * </ul>
-     */
+    /** {@inheritDoc} */
     @Override
     public double cumulativeProbability(double x)  {
         if (x <= a) {
@@ -226,7 +203,7 @@ public final class TriangularDistribution extends AbstractContinuousDistribution
      * {@inheritDoc}
      *
      * <p>For lower limit {@code a}, upper limit {@code b}, and mode {@code c},
-     * the mean is {@code (a + b + c) / 3}.
+     * the mean is \( (a + b + c) / 3 \).
      */
     @Override
     public double getMean() {
@@ -237,7 +214,7 @@ public final class TriangularDistribution extends AbstractContinuousDistribution
      * {@inheritDoc}
      *
      * <p>For lower limit {@code a}, upper limit {@code b}, and mode {@code c},
-     * the variance is {@code (a^2 + b^2 + c^2 - a * b - a * c - b * c) / 18}.
+     * the variance is \( (a^2 + b^2 + c^2 - ab - ac - bc) / 18 \).
      */
     @Override
     public double getVariance() {


[commons-statistics] 01/02: Statistics-25: Remove T-dist switch to normal CDF

Posted by ah...@apache.org.
This is an automated email from the ASF dual-hosted git repository.

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

commit 3ee52f7ca0883495e0df1ca2a914ad24b5ba968a
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Sat Nov 12 16:46:15 2022 +0000

    Statistics-25: Remove T-dist switch to normal CDF
---
 .../apache/commons/statistics/distribution/TDistribution.java  | 10 ----------
 1 file changed, 10 deletions(-)

diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TDistribution.java
index e828276..898b414 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TDistribution.java
@@ -110,10 +110,6 @@ public abstract class TDistribution extends AbstractContinuousDistribution {
     private static class StudentsTDistribution extends TDistribution {
         /** 2. */
         private static final double TWO = 2;
-        /** Number of degrees of freedom above which to use the normal distribution.
-         * This is used to check the CDF when the degrees of freedom is large.
-         * Set to 1 / machine epsilon, 2^52, or 4.50e15. */
-        private static final double DOF_THRESHOLD_NORMAL = 0x1.0p52;
         /** The threshold for the density function where the
          * power function base minus 1 is close to zero. */
         private static final double CLOSE_TO_ZERO = 0.25;
@@ -185,12 +181,6 @@ public abstract class TDistribution extends AbstractContinuousDistribution {
             }
             final double v = getDegreesOfFreedom();
 
-            // This threshold may no longer be required.
-            // See STATISTICS-25.
-            if (v > DOF_THRESHOLD_NORMAL) {
-                return STANDARD_NORMAL.cumulativeProbability(x);
-            }
-
             // cdf(t) = 1 - 0.5 * I_x(t)(v/2, 1/2)
             // where x(t) = v / (v + t^2)
             //