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Posted to commits@commons.apache.org by ah...@apache.org on 2021/12/17 21:46:16 UTC
[commons-statistics] branch master updated (3b33732 -> b525a54)
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 3b33732 Correct javadoc for isSupportConnected
new 65e547c Add PDF and PMF to distribution class javadoc
new 670ad0a Update exponential distribution PDF
new 4ac4925 Create consistent web links in distribution class javadoc.
new 56b1074 Update javadoc for mean and variance
new b525a54 Consistent javadoc for the lower/upper bounds/mean/variance
The 5 revisions listed above as "new" are entirely new to this
repository and will be described in separate emails. The revisions
listed as "add" were already present in the repository and have only
been added to this reference.
Summary of changes:
.../AbstractContinuousDistribution.java | 2 +-
.../distribution/AbstractDiscreteDistribution.java | 2 +-
.../statistics/distribution/BetaDistribution.java | 19 +-
.../distribution/BinomialDistribution.java | 21 +-
.../distribution/CauchyDistribution.java | 31 +-
.../distribution/ChiSquaredDistribution.java | 23 +-
.../distribution/ContinuousDistribution.java | 4 +-
.../distribution/DiscreteDistribution.java | 4 +-
.../distribution/ExponentialDistribution.java | 54 +-
.../statistics/distribution/ExtendedPrecision.java | 2 +-
.../statistics/distribution/FDistribution.java | 30 +-
.../statistics/distribution/GammaDistribution.java | 25 +-
.../distribution/GeometricDistribution.java | 19 +-
.../distribution/GumbelDistribution.java | 29 +-
.../distribution/HypergeometricDistribution.java | 18 +-
.../distribution/LaplaceDistribution.java | 25 +-
.../statistics/distribution/LevyDistribution.java | 26 +-
.../distribution/LogNormalDistribution.java | 38 +-
.../distribution/LogisticDistribution.java | 25 +-
.../distribution/NakagamiDistribution.java | 22 +-
.../distribution/NormalDistribution.java | 25 +-
.../distribution/ParetoDistribution.java | 15 +-
.../distribution/PascalDistribution.java | 53 +-
.../distribution/PoissonDistribution.java | 23 +-
.../distribution/RegularizedBetaUtils.java | 2 +-
.../statistics/distribution/TDistribution.java | 31 +-
.../distribution/TriangularDistribution.java | 21 +-
.../distribution/TruncatedNormalDistribution.java | 25 +-
.../UniformContinuousDistribution.java | 18 +-
.../distribution/UniformDiscreteDistribution.java | 19 +-
.../distribution/WeibullDistribution.java | 63 +-
.../statistics/distribution/ZipfDistribution.java | 36 +-
.../distribution/ExponentialDistributionTest.java | 14 +
.../commons/statistics/distribution/exppdf.csv | 3104 ++++++++++++++++++++
34 files changed, 3595 insertions(+), 273 deletions(-)
create mode 100644 commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/exppdf.csv
[commons-statistics] 05/05: Consistent javadoc for the lower/upper bounds/mean/variance
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 b525a546d2ebedc059f0cb5aad8d5d1d38103e01
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Fri Dec 17 21:41:08 2021 +0000
Consistent javadoc for the lower/upper bounds/mean/variance
If the bounds are defined for all parameters then put this value in the
return statement.
---
.../statistics/distribution/BetaDistribution.java | 8 ++++----
.../statistics/distribution/BinomialDistribution.java | 4 ++--
.../statistics/distribution/CauchyDistribution.java | 18 ++++++++----------
.../distribution/ChiSquaredDistribution.java | 10 ++++------
.../distribution/ExponentialDistribution.java | 16 +++++-----------
.../commons/statistics/distribution/FDistribution.java | 9 ++++-----
.../statistics/distribution/GammaDistribution.java | 11 ++++-------
.../statistics/distribution/GeometricDistribution.java | 4 ++--
.../statistics/distribution/GumbelDistribution.java | 12 ++++--------
.../statistics/distribution/LaplaceDistribution.java | 12 ++++--------
.../statistics/distribution/LevyDistribution.java | 12 +++++++-----
.../statistics/distribution/LogNormalDistribution.java | 10 ++++------
.../statistics/distribution/LogisticDistribution.java | 12 ++++--------
.../statistics/distribution/NakagamiDistribution.java | 10 ++++------
.../statistics/distribution/NormalDistribution.java | 12 ++++--------
.../statistics/distribution/ParetoDistribution.java | 6 +++---
.../statistics/distribution/PascalDistribution.java | 6 +++---
.../statistics/distribution/PoissonDistribution.java | 11 ++++-------
.../commons/statistics/distribution/TDistribution.java | 8 +++-----
.../distribution/TriangularDistribution.java | 4 ----
.../distribution/TruncatedNormalDistribution.java | 14 ++++++++++++--
.../distribution/UniformContinuousDistribution.java | 4 ----
.../distribution/UniformDiscreteDistribution.java | 4 ----
.../statistics/distribution/WeibullDistribution.java | 10 ++++------
.../statistics/distribution/ZipfDistribution.java | 6 +++---
25 files changed, 96 insertions(+), 137 deletions(-)
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BetaDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BetaDistribution.java
index 0c08cbc..cbde35c 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BetaDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BetaDistribution.java
@@ -202,9 +202,9 @@ public final class BetaDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always 0 no matter the parameters.
+ * <p>The lower bound of the support is always 0.
*
- * @return lower bound of the support (always 0)
+ * @return 0.
*/
@Override
public double getSupportLowerBound() {
@@ -214,9 +214,9 @@ public final class BetaDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The upper bound of the support is always 1 no matter the parameters.
+ * <p>The upper bound of the support is always 1.
*
- * @return upper bound of the support (always 1)
+ * @return 1.
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BinomialDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BinomialDistribution.java
index 766d8f5..54607b6 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BinomialDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BinomialDistribution.java
@@ -162,7 +162,7 @@ public final class BinomialDistribution extends AbstractDiscreteDistribution {
* <p>The lower bound of the support is always 0 except for the probability
* parameter {@code p = 1}.
*
- * @return lower bound of the support (0 or the number of trials)
+ * @return 0 or the number of trials.
*/
@Override
public int getSupportLowerBound() {
@@ -175,7 +175,7 @@ public final class BinomialDistribution extends AbstractDiscreteDistribution {
* <p>The upper bound of the support is the number of trials except for the
* probability parameter {@code p = 0}.
*
- * @return upper bound of the support (number of trials or 0)
+ * @return number of trials or 0.
*/
@Override
public int getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java
index 35f11e5..2abf7f5 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java
@@ -154,9 +154,9 @@ public final class CauchyDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The mean is always undefined no matter the parameters.
+ * <p>The mean is always undefined.
*
- * @return NaN
+ * @return NaN.
*/
@Override
public double getMean() {
@@ -166,9 +166,9 @@ public final class CauchyDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The variance is always undefined no matter the parameters.
+ * <p>The variance is always undefined.
*
- * @return NaN
+ * @return NaN.
*/
@Override
public double getVariance() {
@@ -178,10 +178,9 @@ public final class CauchyDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always negative infinity no matter
- * the parameters.
+ * <p>The lower bound of the support is always negative infinity.
*
- * @return lower bound of the support (always Double.NEGATIVE_INFINITY)
+ * @return negative infinity.
*/
@Override
public double getSupportLowerBound() {
@@ -191,10 +190,9 @@ public final class CauchyDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The upper bound of the support is always positive infinity no matter
- * the parameters.
+ * <p>The upper bound of the support is always positive infinity.
*
- * @return upper bound of the support (always Double.POSITIVE_INFINITY)
+ * @return positive infinity.
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ChiSquaredDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ChiSquaredDistribution.java
index a768ecd..5e11d74 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ChiSquaredDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ChiSquaredDistribution.java
@@ -138,10 +138,9 @@ public final class ChiSquaredDistribution extends AbstractContinuousDistribution
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always 0 no matter the
- * degrees of freedom.
+ * <p>The lower bound of the support is always 0.
*
- * @return zero.
+ * @return 0.
*/
@Override
public double getSupportLowerBound() {
@@ -151,10 +150,9 @@ public final class ChiSquaredDistribution extends AbstractContinuousDistribution
/**
* {@inheritDoc}
*
- * <p>The upper bound of the support is always positive infinity no matter the
- * degrees of freedom.
+ * <p>The upper bound of the support is always positive infinity.
*
- * @return {@code Double.POSITIVE_INFINITY}.
+ * @return positive infinity.
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java
index 1709fce..a4ba8b9 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java
@@ -138,11 +138,7 @@ public final class ExponentialDistribution extends AbstractContinuousDistributio
return 0 - mean * Math.log(p);
}
- /**
- * {@inheritDoc}
- *
- * @return the mean
- */
+ /** {@inheritDoc} */
@Override
public double getMean() {
return mean;
@@ -152,7 +148,6 @@ public final class ExponentialDistribution extends AbstractContinuousDistributio
* {@inheritDoc}
*
* <p>For mean {@code k}, the variance is {@code k^2}.
- * @return the variance
*/
@Override
public double getVariance() {
@@ -162,9 +157,9 @@ public final class ExponentialDistribution extends AbstractContinuousDistributio
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always 0 no matter the mean parameter.
+ * <p>The lower bound of the support is always 0.
*
- * @return lower bound of the support (always 0)
+ * @return 0.
*/
@Override
public double getSupportLowerBound() {
@@ -174,10 +169,9 @@ public final class ExponentialDistribution extends AbstractContinuousDistributio
/**
* {@inheritDoc}
*
- * <p>The upper bound of the support is always positive infinity
- * no matter the mean parameter.
+ * <p>The upper bound of the support is always positive infinity.
*
- * @return upper bound of the support (always Double.POSITIVE_INFINITY)
+ * @return positive infinity.
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java
index 942ca90..e1b8ca1 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java
@@ -260,9 +260,9 @@ public final class FDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always 0 no matter the parameters.
+ * <p>The lower bound of the support is always 0.
*
- * @return lower bound of the support (always 0)
+ * @return 0.
*/
@Override
public double getSupportLowerBound() {
@@ -272,10 +272,9 @@ public final class FDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The upper bound of the support is always positive infinity
- * no matter the parameters.
+ * <p>The upper bound of the support is always positive infinity.
*
- * @return upper bound of the support (always Double.POSITIVE_INFINITY)
+ * @return positive infinity.
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GammaDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GammaDistribution.java
index cfe4ab9..b1c173a 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GammaDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GammaDistribution.java
@@ -205,8 +205,6 @@ public final class GammaDistribution extends AbstractContinuousDistribution {
*
* <p>For shape parameter {@code alpha} and scale parameter {@code beta}, the
* variance is {@code alpha * beta^2}.
- *
- * @return {@inheritDoc}
*/
@Override
public double getVariance() {
@@ -216,9 +214,9 @@ public final class GammaDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always 0 no matter the parameters.
+ * <p>The lower bound of the support is always 0.
*
- * @return lower bound of the support (always 0)
+ * @return 0.
*/
@Override
public double getSupportLowerBound() {
@@ -228,10 +226,9 @@ public final class GammaDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The upper bound of the support is always positive infinity
- * no matter the parameters.
+ * <p>The upper bound of the support is always positive infinity.
*
- * @return upper bound of the support (always Double.POSITIVE_INFINITY)
+ * @return positive infinity.
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GeometricDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GeometricDistribution.java
index f9ed53b..251ebea 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GeometricDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GeometricDistribution.java
@@ -229,7 +229,7 @@ public final class GeometricDistribution extends AbstractDiscreteDistribution {
*
* <p>The lower bound of the support is always 0.
*
- * @return lower bound of the support (always 0)
+ * @return 0.
*/
@Override
public int getSupportLowerBound() {
@@ -242,7 +242,7 @@ public final class GeometricDistribution extends AbstractDiscreteDistribution {
* <p>The upper bound of the support is positive infinity except for the
* probability parameter {@code p = 1.0}.
*
- * @return upper bound of the support ({@code Integer.MAX_VALUE} or 0)
+ * @return {@code Integer.MAX_VALUE} or 0.
*/
@Override
public int getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GumbelDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GumbelDistribution.java
index decdc2e..ca7f549 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GumbelDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GumbelDistribution.java
@@ -182,11 +182,9 @@ public final class GumbelDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always negative infinity
- * no matter the parameters.
+ * <p>The lower bound of the support is always negative infinity.
*
- * @return lower bound of the support (always
- * {@code Double.NEGATIVE_INFINITY})
+ * @return negative infinity.
*/
@Override
public double getSupportLowerBound() {
@@ -196,11 +194,9 @@ public final class GumbelDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The upper bound of the support is always positive infinity
- * no matter the parameters.
+ * <p>The upper bound of the support is always positive infinity.
*
- * @return upper bound of the support (always
- * {@code Double.POSITIVE_INFINITY})
+ * @return positive infinity.
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LaplaceDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LaplaceDistribution.java
index 5201355..f115bc4 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LaplaceDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LaplaceDistribution.java
@@ -163,11 +163,9 @@ public final class LaplaceDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always negative infinity
- * no matter the parameters.
+ * <p>The lower bound of the support is always negative infinity.
*
- * @return lower bound of the support (always
- * {@code Double.NEGATIVE_INFINITY})
+ * @return negative infinity.
*/
@Override
public double getSupportLowerBound() {
@@ -177,11 +175,9 @@ public final class LaplaceDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The upper bound of the support is always positive infinity
- * no matter the parameters.
+ * <p>The upper bound of the support is always positive infinity.
*
- * @return upper bound of the support (always
- * {@code Double.POSITIVE_INFINITY})
+ * @return positive infinity.
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LevyDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LevyDistribution.java
index 876e506..5d90174 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LevyDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LevyDistribution.java
@@ -182,6 +182,8 @@ public final class LevyDistribution extends AbstractContinuousDistribution {
* {@inheritDoc}
*
* <p>The mean is equal to positive infinity.
+ *
+ * @return positive infinity.
*/
@Override
public double getMean() {
@@ -192,6 +194,8 @@ public final class LevyDistribution extends AbstractContinuousDistribution {
* {@inheritDoc}
*
* <p>The variance is equal to positive infinity.
+ *
+ * @return positive infinity.
*/
@Override
public double getVariance() {
@@ -203,7 +207,7 @@ public final class LevyDistribution extends AbstractContinuousDistribution {
*
* <p>The lower bound of the support is the {@link #getLocation() location}.
*
- * @return lower bound of the support
+ * @return location.
*/
@Override
public double getSupportLowerBound() {
@@ -213,11 +217,9 @@ public final class LevyDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The upper bound of the support is always positive infinity
- * no matter the parameters.
+ * <p>The upper bound of the support is always positive infinity.
*
- * @return upper bound of the support (always
- * {@code Double.POSITIVE_INFINITY})
+ * @return positive infinity.
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogNormalDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogNormalDistribution.java
index 2426e4b..71247d7 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogNormalDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogNormalDistribution.java
@@ -235,9 +235,9 @@ public final class LogNormalDistribution extends AbstractContinuousDistribution
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always 0 no matter the parameters.
+ * <p>The lower bound of the support is always 0.
*
- * @return lower bound of the support (always 0)
+ * @return 0.
*/
@Override
public double getSupportLowerBound() {
@@ -247,11 +247,9 @@ public final class LogNormalDistribution extends AbstractContinuousDistribution
/**
* {@inheritDoc}
*
- * <p>The upper bound of the support is always positive infinity
- * no matter the parameters.
+ * <p>The upper bound of the support is always positive infinity.
*
- * @return upper bound of the support (always
- * {@code Double.POSITIVE_INFINITY})
+ * @return positive infinity.
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogisticDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogisticDistribution.java
index 0495f16..0aca8fb 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogisticDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogisticDistribution.java
@@ -187,11 +187,9 @@ public final class LogisticDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always negative infinity
- * no matter the parameters.
+ * <p>The lower bound of the support is always negative infinity.
*
- * @return lower bound of the support (always
- * {@code Double.NEGATIVE_INFINITY})
+ * @return negative infinity.
*/
@Override
public double getSupportLowerBound() {
@@ -201,11 +199,9 @@ public final class LogisticDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The upper bound of the support is always positive infinity
- * no matter the parameters.
+ * <p>The upper bound of the support is always positive infinity.
*
- * @return upper bound of the support (always
- * {@code Double.POSITIVE_INFINITY})
+ * @return positive infinity.
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NakagamiDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NakagamiDistribution.java
index 7d3f406..b1209eb 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NakagamiDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NakagamiDistribution.java
@@ -162,9 +162,9 @@ public final class NakagamiDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always 0 no matter parameters.
+ * <p>The lower bound of the support is always 0.
*
- * @return lower bound of the support (always 0)
+ * @return 0.
*/
@Override
public double getSupportLowerBound() {
@@ -174,11 +174,9 @@ public final class NakagamiDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The upper bound of the support is always positive infinity
- * no matter the parameters.
+ * <p>The upper bound of the support is always positive infinity.
*
- * @return upper bound of the support (always
- * {@code Double.POSITIVE_INFINITY})
+ * @return positive infinity.
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NormalDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NormalDistribution.java
index 1d93acb..af8dae7 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NormalDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NormalDistribution.java
@@ -184,11 +184,9 @@ public final class NormalDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always negative infinity
- * no matter the parameters.
+ * <p>The lower bound of the support is always negative infinity.
*
- * @return lower bound of the support (always
- * {@code Double.NEGATIVE_INFINITY})
+ * @return negative infinity.
*/
@Override
public double getSupportLowerBound() {
@@ -198,11 +196,9 @@ public final class NormalDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The upper bound of the support is always positive infinity
- * no matter the parameters.
+ * <p>The upper bound of the support is always positive infinity.
*
- * @return upper bound of the support (always
- * {@code Double.POSITIVE_INFINITY})
+ * @return positive infinity.
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java
index f9dcfe7..47a4ee2 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java
@@ -270,7 +270,7 @@ public final class ParetoDistribution extends AbstractContinuousDistribution {
* <p>
* The lower bound of the support is equal to the scale parameter {@code k}.
*
- * @return lower bound of the support
+ * @return scale.
*/
@Override
public double getSupportLowerBound() {
@@ -280,9 +280,9 @@ public final class ParetoDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
* <p>
- * The upper bound of the support is always positive infinity no matter the parameters.
+ * The upper bound of the support is always positive infinity.
*
- * @return upper bound of the support (always {@code Double.POSITIVE_INFINITY})
+ * @return positive infinity.
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PascalDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PascalDistribution.java
index 136f867..46dd32f 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PascalDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PascalDistribution.java
@@ -211,9 +211,9 @@ public final class PascalDistribution extends AbstractDiscreteDistribution {
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always 0 no matter the parameters.
+ * <p>The lower bound of the support is always 0.
*
- * @return lower bound of the support (always 0)
+ * @return 0.
*/
@Override
public int getSupportLowerBound() {
@@ -226,7 +226,7 @@ public final class PascalDistribution extends AbstractDiscreteDistribution {
* <p>The upper bound of the support is positive infinity except for the
* probability parameter {@code p = 1.0}.
*
- * @return upper bound of the support ({@code Integer.MAX_VALUE} or 0)
+ * @return {@code Integer.MAX_VALUE} or 0.
*/
@Override
public int getSupportUpperBound() {
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 9224ad1..1ad278c 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
@@ -127,9 +127,9 @@ public final class PoissonDistribution extends AbstractDiscreteDistribution {
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always 0 no matter the mean parameter.
+ * <p>The lower bound of the support is always 0.
*
- * @return lower bound of the support (always 0)
+ * @return 0.
*/
@Override
public int getSupportLowerBound() {
@@ -139,12 +139,9 @@ public final class PoissonDistribution extends AbstractDiscreteDistribution {
/**
* {@inheritDoc}
*
- * <p>The upper bound of the support is positive infinity,
- * regardless of the parameter values. There is no integer infinity,
- * so this method returns {@code Integer.MAX_VALUE}.
+ * <p>The upper bound of the support is always positive infinity.
*
- * @return upper bound of the support (always {@code Integer.MAX_VALUE} for
- * positive infinity)
+ * @return {@code Integer.MAX_VALUE}
*/
@Override
public int getSupportUpperBound() {
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 299f18e..c7143d5 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
@@ -298,10 +298,9 @@ public abstract class TDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always negative infinity..
+ * <p>The lower bound of the support is always negative infinity.
*
- * @return lower bound of the support (always
- * {@code Double.NEGATIVE_INFINITY})
+ * @return negative infinity.
*/
@Override
public double getSupportLowerBound() {
@@ -313,8 +312,7 @@ public abstract class TDistribution extends AbstractContinuousDistribution {
*
* <p>The upper bound of the support is always positive infinity.
*
- * @return upper bound of the support (always
- * {@code Double.POSITIVE_INFINITY})
+ * @return positive infinity.
*/
@Override
public double getSupportUpperBound() {
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 058c4ae..c86af09 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
@@ -249,8 +249,6 @@ public final class TriangularDistribution extends AbstractContinuousDistribution
*
* <p>The lower bound of the support is equal to the lower limit parameter
* {@code a} of the distribution.
- *
- * @return lower bound of the support
*/
@Override
public double getSupportLowerBound() {
@@ -262,8 +260,6 @@ public final class TriangularDistribution extends AbstractContinuousDistribution
*
* <p>The upper bound of the support is equal to the upper limit parameter
* {@code b} of the distribution.
- *
- * @return upper bound of the support
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TruncatedNormalDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TruncatedNormalDistribution.java
index d36fac6..fa24538 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TruncatedNormalDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TruncatedNormalDistribution.java
@@ -247,13 +247,23 @@ public final class TruncatedNormalDistribution extends AbstractContinuousDistrib
return variance(a, b) * s * s;
}
- /** {@inheritDoc} */
+ /**
+ * {@inheritDoc}
+ *
+ * <p>The lower bound of the support is equal to the lower bound parameter
+ * of the distribution.
+ */
@Override
public double getSupportLowerBound() {
return lower;
}
- /** {@inheritDoc} */
+ /**
+ * {@inheritDoc}
+ *
+ * <p>The upper bound of the support is equal to the upper bound parameter
+ * of the distribution.
+ */
@Override
public double getSupportUpperBound() {
return upper;
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformContinuousDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformContinuousDistribution.java
index 2787070..063f541 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformContinuousDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformContinuousDistribution.java
@@ -191,8 +191,6 @@ public final class UniformContinuousDistribution extends AbstractContinuousDistr
*
* <p>The lower bound of the support is equal to the lower bound parameter
* of the distribution.
- *
- * @return lower bound of the support
*/
@Override
public double getSupportLowerBound() {
@@ -204,8 +202,6 @@ public final class UniformContinuousDistribution extends AbstractContinuousDistr
*
* <p>The upper bound of the support is equal to the upper bound parameter
* of the distribution.
- *
- * @return upper bound of the support
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformDiscreteDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformDiscreteDistribution.java
index 1b6c528..25c3116 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformDiscreteDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformDiscreteDistribution.java
@@ -242,8 +242,6 @@ public final class UniformDiscreteDistribution extends AbstractDiscreteDistribut
*
* <p>The lower bound of the support is equal to the lower bound parameter
* of the distribution.
- *
- * @return lower bound of the support
*/
@Override
public int getSupportLowerBound() {
@@ -255,8 +253,6 @@ public final class UniformDiscreteDistribution extends AbstractDiscreteDistribut
*
* <p>The upper bound of the support is equal to the upper bound parameter
* of the distribution.
- *
- * @return upper bound of the support
*/
@Override
public int getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/WeibullDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/WeibullDistribution.java
index eb29633..d0ef1d3 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/WeibullDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/WeibullDistribution.java
@@ -268,9 +268,9 @@ public final class WeibullDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always 0 no matter the parameters.
+ * <p>The lower bound of the support is always 0.
*
- * @return lower bound of the support (always 0)
+ * @return 0.
*/
@Override
public double getSupportLowerBound() {
@@ -280,11 +280,9 @@ public final class WeibullDistribution extends AbstractContinuousDistribution {
/**
* {@inheritDoc}
*
- * <p>The upper bound of the support is always positive infinity
- * no matter the parameters.
+ * <p>The upper bound of the support is always positive infinity.
*
- * @return upper bound of the support (always
- * {@code Double.POSITIVE_INFINITY})
+ * @return positive infinity.
*/
@Override
public double getSupportUpperBound() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ZipfDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ZipfDistribution.java
index 15c7412..c7ceb49 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ZipfDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ZipfDistribution.java
@@ -245,9 +245,9 @@ public final class ZipfDistribution extends AbstractDiscreteDistribution {
/**
* {@inheritDoc}
*
- * <p>The lower bound of the support is always 1 no matter the parameters.
+ * <p>The lower bound of the support is always 1.
*
- * @return lower bound of the support (always 1)
+ * @return 1.
*/
@Override
public int getSupportLowerBound() {
@@ -259,7 +259,7 @@ public final class ZipfDistribution extends AbstractDiscreteDistribution {
*
* <p>The upper bound of the support is the number of elements.
*
- * @return upper bound of the support
+ * @return number of elements.
*/
@Override
public int getSupportUpperBound() {
[commons-statistics] 02/05: Update exponential distribution PDF
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 670ad0a5119c21c203f46cbe90fe09bf6950a9cd
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Fri Dec 17 00:50:14 2021 +0000
Update exponential distribution PDF
Directly implement the PDF using exp and do not use exp(logDensity(x)).
This is more accurate on extended precision test data.
Remove check that x >= +infinity in the log density. The result is the
same (-infinity) without this edge case check.
---
.../distribution/ExponentialDistribution.java | 11 +-
.../distribution/ExponentialDistributionTest.java | 14 +
.../commons/statistics/distribution/exppdf.csv | 3104 ++++++++++++++++++++
3 files changed, 3123 insertions(+), 6 deletions(-)
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java
index 93d51d2..123dba6 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java
@@ -70,17 +70,18 @@ public final class ExponentialDistribution extends AbstractContinuousDistributio
/** {@inheritDoc} */
@Override
public double density(double x) {
- return Math.exp(logDensity(x));
+ if (x < SUPPORT_LO) {
+ return 0;
+ }
+ return Math.exp(-x / mean) / mean;
}
/** {@inheritDoc} **/
@Override
public double logDensity(double x) {
- if (x < SUPPORT_LO ||
- x >= SUPPORT_HI) {
+ if (x < SUPPORT_LO) {
return Double.NEGATIVE_INFINITY;
}
-
return -x / mean - logMean;
}
@@ -99,7 +100,6 @@ public final class ExponentialDistribution extends AbstractContinuousDistributio
if (x <= SUPPORT_LO) {
return 0;
}
-
return -Math.expm1(-x / mean);
}
@@ -109,7 +109,6 @@ public final class ExponentialDistribution extends AbstractContinuousDistributio
if (x <= SUPPORT_LO) {
return 1;
}
-
return Math.exp(-x / mean);
}
diff --git a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java
index 8726b8a..a9b8a7e 100644
--- a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java
+++ b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java
@@ -16,9 +16,12 @@
*/
package org.apache.commons.statistics.distribution;
+import java.math.BigDecimal;
import org.apache.commons.numbers.core.Precision;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.CsvFileSource;
/**
* Test cases for {@link ExponentialDistribution}.
@@ -76,4 +79,15 @@ class ExponentialDistributionTest extends BaseContinuousDistributionTest {
Assertions.assertEquals(0.0, d1.inverseCumulativeProbability(0.0));
Assertions.assertEquals(0.0, d1.inverseCumulativeProbability(-0.0));
}
+
+ @ParameterizedTest
+ @CsvFileSource(resources = "exppdf.csv")
+ void testPDF(double mean, double x, BigDecimal expected) {
+ final double e = expected.doubleValue();
+ final double a = ExponentialDistribution.of(mean).density(x);
+ // Require high precision.
+ // This has max error of 3 ulp if using exp(logDensity(x)).
+ Assertions.assertEquals(e, a, Math.ulp(e),
+ () -> "ULP error: " + expected.subtract(new BigDecimal(a)).doubleValue() / Math.ulp(e));
+ }
}
diff --git a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/exppdf.csv b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/exppdf.csv
new file mode 100644
index 0000000..2d88c22
--- /dev/null
+++ b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/exppdf.csv
@@ -0,0 +1,3104 @@
+# 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.
+
+# High-precision test data for the exponential distribution PDF
+# Computed using the following maxima script:
+#
+# fpprec : 128;
+# f(mean, x) := bfloat(exp(-x / mean) / mean);
+# str(x) := ssubst("e","b",string(x));
+#
+# out : openw("exppdf.csv");
+# x : float(makelist(i / 128, i, 1, 128 * 12));
+# /* 2657 / 2^10 */
+# mean : 2.5947265625;
+# for i in x do printf(out, "~f, ~f, ~a~%", mean, i, str(f(mean, i))), fpprintprec : 30;
+# /* 1623468236L / 2^28 */
+# mean : 6.047890469431877;
+# for i in x do printf(out, "~f, ~f, ~a~%", mean, i, str(f(mean, i))), fpprintprec : 30;
+# close(out);
+
+2.5947265625, 0.0078125, 3.84238411900902687712289207411e-1
+2.5947265625, 0.015625, 3.83083242800390189053416634124e-1
+2.5947265625, 0.0234375, 3.81931546584444725489504435245e-1
+2.5947265625, 0.03125, 3.80783312812233709632181444249e-1
+2.5947265625, 0.0390625, 3.79638531074313834157152314219e-1
+2.5947265625, 0.046875, 3.78497190992536314269045760739e-1
+2.5947265625, 0.0546875, 3.77359282219953406922741123708e-1
+2.5947265625, 0.0625, 3.76224794440723986355123997782e-1
+2.5947265625, 0.0703125, 3.75093717370020562906773875511e-1
+2.5947265625, 0.078125, 3.73966040753935635709837015384e-1
+2.5947265625, 0.0859375, 3.72841754369389155598923935031e-1
+2.5947265625, 0.09375, 3.71720848024035321888192129336e-1
+2.5947265625, 0.1015625, 3.70603311556170544882604644954e-1
+2.5947265625, 0.109375, 3.69489134834641352878037423579e-1
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+2.5947265625, 0.5703125, 3.0935125397687623927112099409e-1
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[commons-statistics] 03/05: Create consistent web links in distribution class javadoc.
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 4ac4925d52821f2dc703ee7e781a5295dd4cbb83
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Fri Dec 17 19:26:14 2021 +0000
Create consistent web links in distribution class javadoc.
Update web links to https where applicable.
---
.../distribution/AbstractContinuousDistribution.java | 2 +-
.../distribution/AbstractDiscreteDistribution.java | 2 +-
.../statistics/distribution/BetaDistribution.java | 8 +++++---
.../statistics/distribution/BinomialDistribution.java | 5 ++++-
.../statistics/distribution/CauchyDistribution.java | 5 ++++-
.../statistics/distribution/ChiSquaredDistribution.java | 5 ++++-
.../statistics/distribution/ExponentialDistribution.java | 16 +++++-----------
.../statistics/distribution/ExtendedPrecision.java | 2 +-
.../commons/statistics/distribution/FDistribution.java | 6 +++---
.../statistics/distribution/GammaDistribution.java | 9 ++++++---
.../statistics/distribution/GeometricDistribution.java | 5 ++++-
.../statistics/distribution/GumbelDistribution.java | 7 +++++--
.../distribution/HypergeometricDistribution.java | 5 ++++-
.../statistics/distribution/LaplaceDistribution.java | 5 +++--
.../statistics/distribution/LevyDistribution.java | 6 ++++--
.../statistics/distribution/LogNormalDistribution.java | 5 ++++-
.../statistics/distribution/LogisticDistribution.java | 5 ++++-
.../statistics/distribution/NakagamiDistribution.java | 4 +++-
.../statistics/distribution/NormalDistribution.java | 5 ++++-
.../statistics/distribution/ParetoDistribution.java | 5 ++++-
.../statistics/distribution/PascalDistribution.java | 11 +++++++----
.../statistics/distribution/PoissonDistribution.java | 5 ++++-
.../statistics/distribution/RegularizedBetaUtils.java | 2 +-
.../commons/statistics/distribution/TDistribution.java | 5 ++++-
.../statistics/distribution/TriangularDistribution.java | 4 ++--
.../distribution/UniformContinuousDistribution.java | 7 ++++++-
.../distribution/UniformDiscreteDistribution.java | 8 ++++++--
.../statistics/distribution/WeibullDistribution.java | 4 ++--
.../statistics/distribution/ZipfDistribution.java | 6 ++++--
29 files changed, 109 insertions(+), 55 deletions(-)
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/AbstractContinuousDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/AbstractContinuousDistribution.java
index 11f8f0c..d6670fd 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/AbstractContinuousDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/AbstractContinuousDistribution.java
@@ -29,7 +29,7 @@ import org.apache.commons.rng.sampling.distribution.InverseTransformContinuousSa
*
* <p>This base class provides a default factory method for creating
* a {@link ContinuousDistribution.Sampler sampler instance} that uses the
- * <a href="http://en.wikipedia.org/wiki/Inverse_transform_sampling">
+ * <a href="https://en.wikipedia.org/wiki/Inverse_transform_sampling">
* inversion method</a> for generating random samples that follow the
* distribution.
*
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/AbstractDiscreteDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/AbstractDiscreteDistribution.java
index 4bb5cbc..e519bbc 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/AbstractDiscreteDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/AbstractDiscreteDistribution.java
@@ -27,7 +27,7 @@ import org.apache.commons.rng.sampling.distribution.InverseTransformDiscreteSamp
*
* <p>This base class provides a default factory method for creating
* a {@link DiscreteDistribution.Sampler sampler instance} that uses the
- * <a href="http://en.wikipedia.org/wiki/Inverse_transform_sampling">
+ * <a href="https://en.wikipedia.org/wiki/Inverse_transform_sampling">
* inversion method</a> for generating random samples that follow the
* distribution.
*
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BetaDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BetaDistribution.java
index 742c929..0c08cbc 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BetaDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BetaDistribution.java
@@ -22,7 +22,7 @@ import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.sampling.distribution.ChengBetaSampler;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Beta_distribution">Beta distribution</a>.
+ * Implementation of the beta distribution.
*
* <p>The probability density function of \( X \) is:
*
@@ -36,8 +36,10 @@ import org.apache.commons.rng.sampling.distribution.ChengBetaSampler;
*
* <p>where \( \Gamma \) is the gamma function.
*
- * <p>
- * \( \alpha \) and \( \beta \) are <em>shape</em> parameters.
+ * <p>\( \alpha \) and \( \beta \) are <em>shape</em> parameters.
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Beta_distribution">Beta distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/BetaDistribution.html">Beta distribution (MathWorld)</a>
*/
public final class BetaDistribution extends AbstractContinuousDistribution {
/** First shape parameter. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BinomialDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BinomialDistribution.java
index 19698e2..766d8f5 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BinomialDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BinomialDistribution.java
@@ -19,7 +19,7 @@ package org.apache.commons.statistics.distribution;
import org.apache.commons.numbers.gamma.RegularizedBeta;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Binomial_distribution">binomial distribution</a>.
+ * Implementation of the binomial distribution.
*
* <p>The probability mass function of \( X \) is:
*
@@ -32,6 +32,9 @@ import org.apache.commons.numbers.gamma.RegularizedBeta;
* <p>\[ \binom{n}{k} = \frac{n!}{k! \, (n-k)!} \]
*
* <p>is the binomial coefficient.
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Binomial_distribution">Binomial distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/BinomialDistribution.html">Binomial distribution (MathWorld)</a>
*/
public final class BinomialDistribution extends AbstractDiscreteDistribution {
/** The number of trials. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java
index 9ec0506..33603e6 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java
@@ -20,7 +20,7 @@ import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.sampling.distribution.StableSampler;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Cauchy_distribution">Cauchy distribution</a>.
+ * Implementation of the Cauchy distribution.
*
* <p>The probability density function of \( X \) is:
*
@@ -29,6 +29,9 @@ import org.apache.commons.rng.sampling.distribution.StableSampler;
* <p>for \( x_0 \) the location,
* \( \gamma > 0 \) the scale, and
* \( x \in (-\infty, \infty) \).
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Cauchy_distribution">Cauchy distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/CauchyDistribution.html">Cauchy distribution (MathWorld)</a>
*/
public final class CauchyDistribution extends AbstractContinuousDistribution {
/** The location of this distribution. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ChiSquaredDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ChiSquaredDistribution.java
index 1261522..a768ecd 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ChiSquaredDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ChiSquaredDistribution.java
@@ -19,7 +19,7 @@ package org.apache.commons.statistics.distribution;
import org.apache.commons.rng.UniformRandomProvider;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Chi-squared_distribution">chi-squared distribution</a>.
+ * Implementation of the chi-squared distribution.
*
* <p>The probability density function of \( X \) is:
*
@@ -28,6 +28,9 @@ import org.apache.commons.rng.UniformRandomProvider;
* <p>for \( k > 0 \) the degrees of freedom,
* \( \Gamma(k/2) \) is the gamma function, and
* \( x \in [0, \infty) \).
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Chi-squared_distribution">Chi-squared distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/Chi-SquaredDistribution.html">Chi-squared distribution (MathWorld)</a>
*/
public final class ChiSquaredDistribution extends AbstractContinuousDistribution {
/** Internal Gamma distribution. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java
index 123dba6..1709fce 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java
@@ -20,7 +20,7 @@ import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.sampling.distribution.ZigguratSampler;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Exponential_distribution">exponential distribution</a>.
+ * Implementation of the exponential distribution.
*
* <p>The probability density function of \( X \) is:
*
@@ -32,6 +32,9 @@ import org.apache.commons.rng.sampling.distribution.ZigguratSampler;
* <p>This implementation uses the scale parameter \( \mu \) which is the mean of the distribution.
* A common alternative parameterization uses the rate parameter \( \lambda \) which is the reciprocal
* of the mean.
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Exponential_distribution">Exponential distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/ExponentialDistribution.html">Exponential distribution (MathWorld)</a>
*/
public final class ExponentialDistribution extends AbstractContinuousDistribution {
/** Support lower bound. */
@@ -85,16 +88,7 @@ public final class ExponentialDistribution extends AbstractContinuousDistributio
return -x / mean - logMean;
}
- /**
- * {@inheritDoc}
- *
- * <p>The implementation of this method is based on:
- * <ul>
- * <li>
- * <a href="http://mathworld.wolfram.com/ExponentialDistribution.html">
- * Exponential Distribution</a>, equation (1).</li>
- * </ul>
- */
+ /** {@inheritDoc} */
@Override
public double cumulativeProbability(double x) {
if (x <= SUPPORT_LO) {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExtendedPrecision.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExtendedPrecision.java
index c12e7d0..4fdbec2 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExtendedPrecision.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExtendedPrecision.java
@@ -227,7 +227,7 @@ final class ExtendedPrecision {
* @param ly Low part of second factor.
* @param xy Product of the factors.
* @return <code>lx * ly - (((xy - hx * hy) - lx * hy) - hx * ly)</code>
- * @see <a href="http://www-2.cs.cmu.edu/afs/cs/project/quake/public/papers/robust-arithmetic.ps">
+ * @see <a href="https://www-2.cs.cmu.edu/afs/cs/project/quake/public/papers/robust-arithmetic.ps">
* Shewchuk (1997) Theorum 18</a>
*/
private static double productLow(double hx, double lx, double hy, double ly, double xy) {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java
index 19b5df3..1a39bd4 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java
@@ -30,8 +30,8 @@ import org.apache.commons.numbers.gamma.RegularizedBeta;
* <p>for \( d_1, d_2 > 0 \) the degrees of freedom, \( \operatorname{B}(d_1 / 2, d_2 / 2) \) is the beta function,
* and \( x \in [0, \infty) \).
*
- * @see <a href="http://en.wikipedia.org/wiki/F-distribution">F-distribution (Wikipedia)</a>
- * @see <a href="http://mathworld.wolfram.com/F-Distribution.html">F-distribution (MathWorld)</a>
+ * @see <a href="https://en.wikipedia.org/wiki/F-distribution">F-distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/F-Distribution.html">F-distribution (MathWorld)</a>
*/
public final class FDistribution extends AbstractContinuousDistribution {
/** Support lower bound. */
@@ -164,7 +164,7 @@ public final class FDistribution extends AbstractContinuousDistribution {
* <p>The implementation of this method is based on
* <ul>
* <li>
- * <a href="http://mathworld.wolfram.com/F-Distribution.html">
+ * <a href="https://mathworld.wolfram.com/F-Distribution.html">
* F-Distribution</a>, equation (4).
* </li>
* </ul>
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GammaDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GammaDistribution.java
index 12f94cd..cfe4ab9 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GammaDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GammaDistribution.java
@@ -22,14 +22,17 @@ import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.sampling.distribution.AhrensDieterMarsagliaTsangGammaSampler;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Gamma_distribution">gamma distribution</a>.
+ * Implementation of the gamma distribution.
*
* <p>The probability density function of \( X \) is:
*
- * <p>\[ f(x;k,\theta) = \frac{x^{k-1}e^{-x/\theta}}{\theta^k\Gamma(k)} \]
+ * <p>\[ f(x;k,\theta) = \frac{x^{k-1}e^{-x/\theta}}{\theta^k\Gamma(k)} \]
*
* <p>for \( k > 0 \) the shape, \( \theta > 0 \) the scale, \( \Gamma(k) \) is the gamma function
* and \( x \in (0, \infty) \).
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Gamma_distribution">Gamma distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/GammaDistribution.html">Gamma distribution (MathWorld)</a>
*/
public final class GammaDistribution extends AbstractContinuousDistribution {
/** Support lower bound. */
@@ -157,7 +160,7 @@ public final class GammaDistribution extends AbstractContinuousDistribution {
* <p>The implementation of this method is based on:
* <ul>
* <li>
- * <a href="http://mathworld.wolfram.com/Chi-SquaredDistribution.html">
+ * <a href="https://mathworld.wolfram.com/Chi-SquaredDistribution.html">
* Chi-Squared Distribution</a>, equation (9).
* </li>
* <li>Casella, G., & Berger, R. (1990). <i>Statistical Inference</i>.
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GeometricDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GeometricDistribution.java
index b7bc116..f9ed53b 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GeometricDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GeometricDistribution.java
@@ -21,7 +21,7 @@ import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.sampling.distribution.GeometricSampler;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Geometric_distribution">geometric distribution</a>.
+ * Implementation of the geometric distribution.
*
* <p>The probability mass function of \( X \) is:
*
@@ -32,6 +32,9 @@ import org.apache.commons.rng.sampling.distribution.GeometricSampler;
*
* <p>This parameterization is used to model the number of failures until
* the first success.
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Geometric_distribution">Geometric distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/GeometricDistribution.html">Geometric distribution (MathWorld)</a>
*/
public final class GeometricDistribution extends AbstractDiscreteDistribution {
/** 1/2. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GumbelDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GumbelDistribution.java
index b44e6e4..decdc2e 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GumbelDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GumbelDistribution.java
@@ -17,7 +17,7 @@
package org.apache.commons.statistics.distribution;
/**
- * This class implements the <a href="http://en.wikipedia.org/wiki/Gumbel_distribution">Gumbel distribution</a>.
+ * Implementation of the Gumbel distribution.
*
* <p>The probability density function of \( X \) is:
*
@@ -28,6 +28,9 @@ package org.apache.commons.statistics.distribution;
* <p>for \( \mu \) the location,
* \( \beta > 0 \) the scale, and
* \( x \in (-\infty, \infty) \).
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Gumbel_distribution">Gumbel distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/GumbelDistribution.html">Gumbel distribution (MathWorld)</a>
*/
public final class GumbelDistribution extends AbstractContinuousDistribution {
/** Support lower bound. */
@@ -158,7 +161,7 @@ public final class GumbelDistribution extends AbstractContinuousDistribution {
* {@inheritDoc}
*
* <p>The mean is {@code mu + gamma * beta}, where {@code gamma} is
- * <a href="http://mathworld.wolfram.com/Euler-MascheroniConstantApproximations.html">
+ * <a href="https://mathworld.wolfram.com/Euler-MascheroniConstantApproximations.html">
* Euler's constant</a>
*/
@Override
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/HypergeometricDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/HypergeometricDistribution.java
index f551a1f..1a5c954 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/HypergeometricDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/HypergeometricDistribution.java
@@ -18,7 +18,7 @@
package org.apache.commons.statistics.distribution;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Hypergeometric_distribution">hypergeometric distribution</a>.
+ * Implementation of the hypergeometric distribution.
*
* <p>The probability mass function of \( X \) is:
*
@@ -32,6 +32,9 @@ package org.apache.commons.statistics.distribution;
* <p>\[ \binom{a}{b} = \frac{a!}{b! \, (a-b)!} \]
*
* <p>is the binomial coefficient.
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Hypergeometric_distribution">Hypergeometric distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/HypergeometricDistribution.html">Hypergeometric distribution (MathWorld)</a>
*/
public final class HypergeometricDistribution extends AbstractDiscreteDistribution {
/** The number of successes in the population. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LaplaceDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LaplaceDistribution.java
index 675a90e..5201355 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LaplaceDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LaplaceDistribution.java
@@ -17,7 +17,7 @@
package org.apache.commons.statistics.distribution;
/**
- * This class implements the Laplace distribution.
+ * Implementation of the Laplace distribution.
*
* <p>The probability density function of \( X \) is:
*
@@ -27,7 +27,8 @@ package org.apache.commons.statistics.distribution;
* \( b > 0 \) the scale, and
* \( x \in (-\infty, \infty) \).
*
- * @see <a href="http://en.wikipedia.org/wiki/Laplace_distribution">Laplace distribution (Wikipedia)</a>
+ * @see <a href="https://en.wikipedia.org/wiki/Laplace_distribution">Laplace distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/LaplaceDistribution.html">Laplace distribution (MathWorld)</a>
*/
public final class LaplaceDistribution extends AbstractContinuousDistribution {
/** The location parameter. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LevyDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LevyDistribution.java
index 83644c6..876e506 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LevyDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LevyDistribution.java
@@ -24,8 +24,7 @@ import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.sampling.distribution.LevySampler;
/**
- * This class implements the <a href="http://en.wikipedia.org/wiki/L%C3%A9vy_distribution">
- * Lévy distribution</a>.
+ * Implementation of the Lévy distribution.
*
* <p>The probability density function of \( X \) is:
*
@@ -34,6 +33,9 @@ import org.apache.commons.rng.sampling.distribution.LevySampler;
* <p>for \( \mu \) the location,
* \( c > 0 \) the scale, and
* \( x \in [\mu, \infty) \).
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/L%C3%A9vy_distribution">Lévy distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/LevyDistribution.html">Lévy distribution (MathWorld)</a>
*/
public final class LevyDistribution extends AbstractContinuousDistribution {
/** 1 / 2(erfc^-1 (0.5))^2. Computed using Matlab's VPA to 30 digits. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogNormalDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogNormalDistribution.java
index fb285d1..2426e4b 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogNormalDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogNormalDistribution.java
@@ -24,7 +24,7 @@ import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.sampling.distribution.ZigguratSampler;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Log-normal_distribution">log-normal distribution</a>.
+ * Implementation of the log-normal distribution.
*
* <p>\( X \) is log-normally distributed if its natural logarithm \( \ln(x) \)
* is normally distributed. The probability density function of \( X \) is:
@@ -35,6 +35,9 @@ import org.apache.commons.rng.sampling.distribution.ZigguratSampler;
* \( \sigma > 0 \) the standard deviation of the normally distributed natural logarithm of this
* distribution, and
* \( x \in (0, \infty) \).
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Log-normal_distribution">Log-normal distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/LogNormalDistribution.html">Log-normal distribution (MathWorld)</a>
*/
public final class LogNormalDistribution extends AbstractContinuousDistribution {
/** 0.5 * ln(2 * pi). Computed to 25-digits precision. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogisticDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogisticDistribution.java
index 57332fe..0495f16 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogisticDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogisticDistribution.java
@@ -17,7 +17,7 @@
package org.apache.commons.statistics.distribution;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Logistic_distribution">logistic distribution</a>.
+ * Implementation of the logistic distribution.
*
* <p>The probability density function of \( X \) is:
*
@@ -26,6 +26,9 @@ package org.apache.commons.statistics.distribution;
* <p>for \( \mu \) the location,
* \( s > 0 \) the scale, and
* \( x \in (-\infty, \infty) \).
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Logistic_distribution">Logistic distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/LogisticDistribution.html">Logistic distribution (MathWorld)</a>
*/
public final class LogisticDistribution extends AbstractContinuousDistribution {
/** Support lower bound. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NakagamiDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NakagamiDistribution.java
index f8c64a5..7d3f406 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NakagamiDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NakagamiDistribution.java
@@ -21,7 +21,7 @@ import org.apache.commons.numbers.gamma.LogGamma;
import org.apache.commons.numbers.gamma.RegularizedGamma;
/**
- * This class implements the <a href="http://en.wikipedia.org/wiki/Nakagami_distribution">Nakagami distribution</a>.
+ * Implementation of the Nakagami distribution.
*
* <p>The probability density function of \( X \) is:
*
@@ -30,6 +30,8 @@ import org.apache.commons.numbers.gamma.RegularizedGamma;
* <p>for \( \mu > 0 \) the shape,
* \( \Omega > 0 \) the scale, and
* \( x \in (0, \infty) \).
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Nakagami_distribution">Nakagami distribution (Wikipedia)</a>
*/
public final class NakagamiDistribution extends AbstractContinuousDistribution {
/** Support lower bound. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NormalDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NormalDistribution.java
index 133d1fa..1d93acb 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NormalDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NormalDistribution.java
@@ -25,7 +25,7 @@ import org.apache.commons.rng.sampling.distribution.GaussianSampler;
import org.apache.commons.rng.sampling.distribution.ZigguratSampler;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Normal_distribution">normal (Gaussian) distribution</a>.
+ * Implementation of the normal (Gaussian) distribution.
*
* <p>The probability density function of \( X \) is:
*
@@ -34,6 +34,9 @@ import org.apache.commons.rng.sampling.distribution.ZigguratSampler;
* <p>for \( \mu \) the mean,
* \( \sigma > 0 \) the standard deviation, and
* \( x \in (-\infty, \infty) \).
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Normal_distribution">Normal distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/NormalDistribution.html">Normal distribution (MathWorld)</a>
*/
public final class NormalDistribution extends AbstractContinuousDistribution {
/** 0.5 * ln(2 * pi). Computed to 25-digits precision. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java
index bc58ec7..f9dcfe7 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java
@@ -22,7 +22,7 @@ import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.sampling.distribution.InverseTransformParetoSampler;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Pareto_distribution">Pareto (Type I) distribution</a>.
+ * Implementation of the Pareto (Type I) distribution.
*
* <p>The probability density function of \( X \) is:
*
@@ -34,6 +34,9 @@ import org.apache.commons.rng.sampling.distribution.InverseTransformParetoSample
*
* <p>\( k \) is a <em>scale</em> parameter: this is the minimum possible value of \( X \).
* <br>\( \alpha \) is a <em>shape</em> parameter: this is the Pareto index.
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Pareto_distribution">Pareto distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/ParetoDistribution.html">Pareto distribution (MathWorld)</a>
*/
public final class ParetoDistribution extends AbstractContinuousDistribution {
/** The minimum value for the shape parameter when computing when computing the variance. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PascalDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PascalDistribution.java
index 40e31e5..136f867 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PascalDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PascalDistribution.java
@@ -21,18 +21,18 @@ import org.apache.commons.numbers.combinatorics.LogBinomialCoefficient;
import org.apache.commons.numbers.gamma.RegularizedBeta;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Negative_binomial_distribution">Pascal distribution.</a>
+ * Implementation of the Pascal distribution.
*
- * <p>The Pascal distribution is a special case of the Negative Binomial distribution
+ * <p>The Pascal distribution is a special case of the negative binomial distribution
* where the number of successes parameter is an integer.
*
* <p>There are various ways to express the probability mass and distribution
* functions for the Pascal distribution. The present implementation represents
* the distribution of the number of failures before \( r \) successes occur.
* This is the convention adopted in e.g.
- * <a href="http://mathworld.wolfram.com/NegativeBinomialDistribution.html">MathWorld</a>,
+ * <a href="https://mathworld.wolfram.com/NegativeBinomialDistribution.html">MathWorld</a>,
* but <em>not</em> in
- * <a href="http://en.wikipedia.org/wiki/Negative_binomial_distribution">Wikipedia</a>.
+ * <a href="https://en.wikipedia.org/wiki/Negative_binomial_distribution">Wikipedia</a>.
*
* <p>The probability mass function of \( X \) is:
*
@@ -55,6 +55,9 @@ import org.apache.commons.numbers.gamma.RegularizedBeta;
* <p>\[ P(X \leq k) = I(p, r, k + 1) \]
*
* <p>where \( I \) is the regularized incomplete beta function.
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Negative_binomial_distribution">Negative binomial distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/NegativeBinomialDistribution.html">Negative binomial distribution (MathWorld)</a>
*/
public final class PascalDistribution extends AbstractDiscreteDistribution {
/** The number of successes. */
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 85a2b1a..9224ad1 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
@@ -24,7 +24,7 @@ import org.apache.commons.rng.sampling.distribution.SharedStateContinuousSampler
import org.apache.commons.rng.sampling.distribution.ZigguratSampler;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Poisson_distribution">Poisson distribution</a>.
+ * Implementation of the Poisson distribution.
*
* <p>The probability mass function of \( X \) is:
*
@@ -32,6 +32,9 @@ import org.apache.commons.rng.sampling.distribution.ZigguratSampler;
*
* <p>for \( \lambda \in (0, \infty) \) the mean and
* \( k \in \{0, 1, 2, \dots\} \) the number of events.
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Poisson_distribution">Poisson distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/PoissonDistribution.html">Poisson distribution (MathWorld)</a>
*/
public final class PoissonDistribution extends AbstractDiscreteDistribution {
/** 0.5 * ln(2 * pi). Computed to 25-digits precision. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/RegularizedBetaUtils.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/RegularizedBetaUtils.java
index 646f77d..c049563 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/RegularizedBetaUtils.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/RegularizedBetaUtils.java
@@ -19,7 +19,7 @@ package org.apache.commons.statistics.distribution;
import org.apache.commons.numbers.gamma.RegularizedBeta;
/**
- * Utilities for the <a href="http://mathworld.wolfram.com/RegularizedBetaFunction.html">
+ * Utilities for the <a href="https://mathworld.wolfram.com/RegularizedBetaFunction.html">
* Regularized Beta function</a> {@code I(x, a, b)}.
*/
final class RegularizedBetaUtils {
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 0eeb1e5..d810509 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
@@ -21,7 +21,7 @@ import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.numbers.gamma.LogGamma;
/**
- * Implementation of <a href='http://en.wikipedia.org/wiki/Student's_t-distribution'>Student's t-distribution</a>.
+ * Implementation of Student's t-distribution.
*
* <p>The probability density function of \( X \) is:
*
@@ -30,6 +30,9 @@ import org.apache.commons.numbers.gamma.LogGamma;
* <p>for \( v > 0 \) the degrees of freedom,
* \( \Gamma \) is the gamma function, and
* \( x \in (-\infty, \infty) \).
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Student%27s_t-distribution">Student's t-distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/Studentst-Distribution.html">Student's t-distribution (MathWorld)</a>
*/
public abstract class TDistribution extends AbstractContinuousDistribution {
/** A standard normal distribution used for calculations.
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 baa18c2..058c4ae 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
@@ -31,8 +31,8 @@ package org.apache.commons.statistics.distribution;
* <p>for \( -\infty \lt a \le c \le b \lt \infty \) and
* \( x \in [a, b] \).
*
- * @see <a href="http://en.wikipedia.org/wiki/Triangular_distribution">
- * Triangular distribution (Wikipedia)</a>
+ * @see <a href="https://en.wikipedia.org/wiki/Triangular_distribution">Triangular distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/TriangularDistribution.html">Triangular distribution (MathWorld)</a>
*/
public final class TriangularDistribution extends AbstractContinuousDistribution {
/** Lower limit of this distribution (inclusive). */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformContinuousDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformContinuousDistribution.java
index d7fccf6..2787070 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformContinuousDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformContinuousDistribution.java
@@ -21,7 +21,7 @@ import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Uniform_distribution_(continuous)">uniform distribution</a>.
+ * Implementation of the uniform distribution.
*
* <p>The probability density function of \( X \) is:
*
@@ -29,6 +29,11 @@ import org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler;
*
* <p>for \( -\infty \lt a \lt b \lt \infty \) and
* \( x \in [a, b] \).
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Uniform_distribution_(continuous)">
+ * Uniform distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/UniformDistribution.html">
+ * Uniform distribution (MathWorld)</a>
*/
public final class UniformContinuousDistribution extends AbstractContinuousDistribution {
/** Lower bound of this distribution (inclusive). */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformDiscreteDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformDiscreteDistribution.java
index 5624324..1b6c528 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformDiscreteDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformDiscreteDistribution.java
@@ -21,8 +21,7 @@ import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.sampling.distribution.DiscreteUniformSampler;
/**
- * Implementation of the <a href="http://en.wikipedia.org/wiki/Uniform_distribution_(discrete)">
- * uniform integer distribution</a>.
+ * Implementation of the uniform discrete distribution.
*
* <p>The probability mass function of \( X \) is:
*
@@ -30,6 +29,11 @@ import org.apache.commons.rng.sampling.distribution.DiscreteUniformSampler;
*
* <p>for integer \( a, b \) and \( a \le b \) and
* \( k \in [a, b] \).
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Uniform_distribution_(discrete)">
+ * Uniform distribution (discrete) (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/DiscreteUniformDistribution.html">
+ * Discrete uniform distribution (MathWorld)</a>
*/
public final class UniformDiscreteDistribution extends AbstractDiscreteDistribution {
/** Lower bound (inclusive) of this distribution. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/WeibullDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/WeibullDistribution.java
index 5ac33e7..eb29633 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/WeibullDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/WeibullDistribution.java
@@ -38,8 +38,8 @@ import org.apache.commons.rng.sampling.distribution.ZigguratSampler;
* <li>\( k = 2 \) is the Rayleigh distribution with scale \( \sigma = \frac {\lambda}{\sqrt{2}} \)
* </ul>
*
- * @see <a href="http://en.wikipedia.org/wiki/Weibull_distribution">Weibull distribution (Wikipedia)</a>
- * @see <a href="http://mathworld.wolfram.com/WeibullDistribution.html">Weibull distribution (MathWorld)</a>
+ * @see <a href="https://en.wikipedia.org/wiki/Weibull_distribution">Weibull distribution (Wikipedia)</a>
+ * @see <a href="https://mathworld.wolfram.com/WeibullDistribution.html">Weibull distribution (MathWorld)</a>
*/
public final class WeibullDistribution extends AbstractContinuousDistribution {
/** Support lower bound. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ZipfDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ZipfDistribution.java
index 0a2f26c..15c7412 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ZipfDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ZipfDistribution.java
@@ -22,7 +22,7 @@ import org.apache.commons.rng.sampling.distribution.DiscreteUniformSampler;
import org.apache.commons.rng.sampling.distribution.RejectionInversionZipfSampler;
/**
- * Implementation of the <a href="https://en.wikipedia.org/wiki/Zipf's_law">Zipf distribution</a>.
+ * Implementation of the Zipf distribution.
*
* <p>The probability mass function of \( X \) is:
*
@@ -34,6 +34,8 @@ import org.apache.commons.rng.sampling.distribution.RejectionInversionZipfSample
* \( H_{N,s} \) is the normalizing constant which corresponds to the
* <a href="https://en.wikipedia.org/wiki/Harmonic_number#Generalized_harmonic_numbers">
* generalized harmonic number</a> of order N of s.
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Zipf's_law">Zipf distribution (Wikipedia)</a>
*/
public final class ZipfDistribution extends AbstractDiscreteDistribution {
/** Number of elements. */
@@ -197,7 +199,7 @@ public final class ZipfDistribution extends AbstractDiscreteDistribution {
/**
* Calculates the Nth generalized harmonic number. See
- * <a href="http://mathworld.wolfram.com/HarmonicSeries.html">Harmonic
+ * <a href="https://mathworld.wolfram.com/HarmonicSeries.html">Harmonic
* Series</a>.
*
* <p>Assumes {@code exponent > 0} to arrange the terms to sum from small to large.
[commons-statistics] 01/05: Add PDF and PMF to distribution class javadoc
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 65e547c4008775953efa7d8a960e8b36d57e213e
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Wed Dec 15 22:36:15 2021 +0000
Add PDF and PMF to distribution class javadoc
---
.../statistics/distribution/BetaDistribution.java | 3 +-
.../distribution/BinomialDistribution.java | 12 ++++++
.../distribution/CauchyDistribution.java | 8 ++++
.../distribution/ChiSquaredDistribution.java | 8 ++++
.../distribution/ExponentialDistribution.java | 11 ++++-
.../statistics/distribution/FDistribution.java | 7 ++++
.../statistics/distribution/GammaDistribution.java | 7 ++++
.../distribution/GeometricDistribution.java | 10 +++++
.../distribution/GumbelDistribution.java | 10 +++++
.../distribution/HypergeometricDistribution.java | 13 ++++++
.../distribution/LaplaceDistribution.java | 8 ++++
.../statistics/distribution/LevyDistribution.java | 8 ++++
.../distribution/LogNormalDistribution.java | 23 ++++------
.../distribution/LogisticDistribution.java | 8 ++++
.../distribution/NakagamiDistribution.java | 8 ++++
.../distribution/NormalDistribution.java | 8 ++++
.../distribution/ParetoDistribution.java | 4 +-
.../distribution/PascalDistribution.java | 38 ++++++++++-------
.../distribution/PoissonDistribution.java | 7 ++++
.../statistics/distribution/TDistribution.java | 8 ++++
.../distribution/TriangularDistribution.java | 13 +++++-
.../distribution/TruncatedNormalDistribution.java | 11 +++++
.../UniformContinuousDistribution.java | 7 ++++
.../distribution/UniformDiscreteDistribution.java | 7 ++++
.../distribution/WeibullDistribution.java | 49 ++++++++++++----------
.../statistics/distribution/ZipfDistribution.java | 24 +++++------
26 files changed, 252 insertions(+), 68 deletions(-)
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BetaDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BetaDistribution.java
index b67425f..742c929 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BetaDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BetaDistribution.java
@@ -28,7 +28,8 @@ import org.apache.commons.rng.sampling.distribution.ChengBetaSampler;
*
* <p>\[ f(x; \alpha, \beta) = \frac{1}{ B(\alpha, \beta)} x^{\alpha-1} (1-x)^{\beta-1} \]
*
- * <p>for \( \alpha > 0 \), \( \beta > 0 \), \( x \in [0, 1] \) and
+ * <p>for \( \alpha > 0 \),
+ * \( \beta > 0 \), \( x \in [0, 1] \), and
* the beta function, \( B \), is a normalization constant:
*
* <p>\[ B(\alpha, \beta) = \frac{\Gamma(\alpha+\beta)}{\Gamma(\alpha) \Gamma(\beta)} \]
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BinomialDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BinomialDistribution.java
index d59e237..19698e2 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BinomialDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/BinomialDistribution.java
@@ -20,6 +20,18 @@ import org.apache.commons.numbers.gamma.RegularizedBeta;
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Binomial_distribution">binomial distribution</a>.
+ *
+ * <p>The probability mass function of \( X \) is:
+ *
+ * <p>\[ f(k; n, p) = \binom{n}{k} p^k (1-p)^{n-k} \]
+ *
+ * <p>for \( n \in \{0, 1, 2, \dots\} \) the number of trials,
+ * \( p \in [0, 1] \) the probability of success,
+ * \( k \in \{0, 1, \dots, n\} \) the number of successes, and
+ *
+ * <p>\[ \binom{n}{k} = \frac{n!}{k! \, (n-k)!} \]
+ *
+ * <p>is the binomial coefficient.
*/
public final class BinomialDistribution extends AbstractDiscreteDistribution {
/** The number of trials. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java
index ca766be..9ec0506 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java
@@ -21,6 +21,14 @@ import org.apache.commons.rng.sampling.distribution.StableSampler;
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Cauchy_distribution">Cauchy distribution</a>.
+ *
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x; x_0, \gamma) = { 1 \over \pi \gamma } \left[ { \gamma^2 \over (x - x_0)^2 + \gamma^2 } \right] \]
+ *
+ * <p>for \( x_0 \) the location,
+ * \( \gamma > 0 \) the scale, and
+ * \( x \in (-\infty, \infty) \).
*/
public final class CauchyDistribution extends AbstractContinuousDistribution {
/** The location of this distribution. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ChiSquaredDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ChiSquaredDistribution.java
index fa86783..1261522 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ChiSquaredDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ChiSquaredDistribution.java
@@ -20,6 +20,14 @@ import org.apache.commons.rng.UniformRandomProvider;
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Chi-squared_distribution">chi-squared distribution</a>.
+ *
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x; k) = \frac{1}{2^{k/2} \Gamma(k/2)} x^{k/2 -1} e^{-x/2} \]
+ *
+ * <p>for \( k > 0 \) the degrees of freedom,
+ * \( \Gamma(k/2) \) is the gamma function, and
+ * \( x \in [0, \infty) \).
*/
public final class ChiSquaredDistribution extends AbstractContinuousDistribution {
/** Internal Gamma distribution. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java
index 1f04867..93d51d2 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java
@@ -22,8 +22,15 @@ import org.apache.commons.rng.sampling.distribution.ZigguratSampler;
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Exponential_distribution">exponential distribution</a>.
*
- * <p>This implementation uses the scale parameter {@code μ} which is the mean of the distribution.
- * A common alternative parameterization uses the rate parameter {@code λ} which is the reciprocal
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x; \mu) = \frac{1}{\mu} e^{-x / \mu} \]
+ *
+ * <p>for \( \mu > 0 \) the mean and
+ * \( x \in [0, \infty) \).
+ *
+ * <p>This implementation uses the scale parameter \( \mu \) which is the mean of the distribution.
+ * A common alternative parameterization uses the rate parameter \( \lambda \) which is the reciprocal
* of the mean.
*/
public final class ExponentialDistribution extends AbstractContinuousDistribution {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java
index b548af7..19b5df3 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java
@@ -23,6 +23,13 @@ import org.apache.commons.numbers.gamma.RegularizedBeta;
/**
* Implementation of the F-distribution.
*
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x; d_1, d_2) = \frac{1}{\operatorname{B}\left(\frac{d_1}{2},\frac{d_2}{2}\right)} \left(\frac{d_1}{d_2}\right)^{d_1/2} x^{d_1/2 - 1} \left(1+\frac{d_1}{d_2} \, x \right)^{-(d_1+d_2)/2} \]
+ *
+ * <p>for \( d_1, d_2 > 0 \) the degrees of freedom, \( \operatorname{B}(d_1 / 2, d_2 / 2) \) is the beta function,
+ * and \( x \in [0, \infty) \).
+ *
* @see <a href="http://en.wikipedia.org/wiki/F-distribution">F-distribution (Wikipedia)</a>
* @see <a href="http://mathworld.wolfram.com/F-Distribution.html">F-distribution (MathWorld)</a>
*/
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GammaDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GammaDistribution.java
index 63bf630..12f94cd 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GammaDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GammaDistribution.java
@@ -23,6 +23,13 @@ import org.apache.commons.rng.sampling.distribution.AhrensDieterMarsagliaTsangGa
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Gamma_distribution">gamma distribution</a>.
+ *
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x;k,\theta) = \frac{x^{k-1}e^{-x/\theta}}{\theta^k\Gamma(k)} \]
+ *
+ * <p>for \( k > 0 \) the shape, \( \theta > 0 \) the scale, \( \Gamma(k) \) is the gamma function
+ * and \( x \in (0, \infty) \).
*/
public final class GammaDistribution extends AbstractContinuousDistribution {
/** Support lower bound. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GeometricDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GeometricDistribution.java
index 7d9e623..b7bc116 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GeometricDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GeometricDistribution.java
@@ -22,6 +22,16 @@ import org.apache.commons.rng.sampling.distribution.GeometricSampler;
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Geometric_distribution">geometric distribution</a>.
+ *
+ * <p>The probability mass function of \( X \) is:
+ *
+ * <p>\[ f(k; p) = (1-p)^k \, p \]
+ *
+ * <p>for \( p \in (0, 1] \) the probability of success and
+ * \( k \in \{0, 1, 2, \dots\} \) the number of failures.
+ *
+ * <p>This parameterization is used to model the number of failures until
+ * the first success.
*/
public final class GeometricDistribution extends AbstractDiscreteDistribution {
/** 1/2. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GumbelDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GumbelDistribution.java
index 59127b3..b44e6e4 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GumbelDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/GumbelDistribution.java
@@ -18,6 +18,16 @@ package org.apache.commons.statistics.distribution;
/**
* This class implements the <a href="http://en.wikipedia.org/wiki/Gumbel_distribution">Gumbel distribution</a>.
+ *
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x; \mu, \beta) = \frac{1}{\beta} e^{-(z+e^{-z})} \]
+ *
+ * <p>where \[ z = \frac{x - \mu}{\beta} \]
+ *
+ * <p>for \( \mu \) the location,
+ * \( \beta > 0 \) the scale, and
+ * \( x \in (-\infty, \infty) \).
*/
public final class GumbelDistribution extends AbstractContinuousDistribution {
/** Support lower bound. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/HypergeometricDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/HypergeometricDistribution.java
index 8d9c1d5..f551a1f 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/HypergeometricDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/HypergeometricDistribution.java
@@ -19,6 +19,19 @@ package org.apache.commons.statistics.distribution;
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Hypergeometric_distribution">hypergeometric distribution</a>.
+ *
+ * <p>The probability mass function of \( X \) is:
+ *
+ * <p>\[ f(k; n, p) = \frac{\binom{K}{k} \binom{N - K}{n-k}}{\binom{N}{n}} \]
+ *
+ * <p>for \( N \in \{0, 1, 2, \dots\} \) the population size,
+ * \( K \in \{0, 1, \dots, N\} \) the number of success states,
+ * \( n \in \{0, 1, \dots, N\} \) the number of samples,
+ * \( k \in \{\max(0, n+K-N), \dots, \min(n, K)\} \) the number of successes, and
+ *
+ * <p>\[ \binom{a}{b} = \frac{a!}{b! \, (a-b)!} \]
+ *
+ * <p>is the binomial coefficient.
*/
public final class HypergeometricDistribution extends AbstractDiscreteDistribution {
/** The number of successes in the population. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LaplaceDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LaplaceDistribution.java
index c66a481..675a90e 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LaplaceDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LaplaceDistribution.java
@@ -19,6 +19,14 @@ package org.apache.commons.statistics.distribution;
/**
* This class implements the Laplace distribution.
*
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x; \mu, b) = \frac{1}{2b} \exp \left( -\frac{|x-\mu|}{b} \right) \]
+ *
+ * <p>for \( \mu \) the location,
+ * \( b > 0 \) the scale, and
+ * \( x \in (-\infty, \infty) \).
+ *
* @see <a href="http://en.wikipedia.org/wiki/Laplace_distribution">Laplace distribution (Wikipedia)</a>
*/
public final class LaplaceDistribution extends AbstractContinuousDistribution {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LevyDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LevyDistribution.java
index d4ab4cf..83644c6 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LevyDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LevyDistribution.java
@@ -26,6 +26,14 @@ import org.apache.commons.rng.sampling.distribution.LevySampler;
/**
* This class implements the <a href="http://en.wikipedia.org/wiki/L%C3%A9vy_distribution">
* Lévy distribution</a>.
+ *
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x; \mu, c) = \sqrt{\frac{c}{2\pi}}~~\frac{e^{ -\frac{c}{2(x-\mu)}}} {(x-\mu)^{3/2}} \]
+ *
+ * <p>for \( \mu \) the location,
+ * \( c > 0 \) the scale, and
+ * \( x \in [\mu, \infty) \).
*/
public final class LevyDistribution extends AbstractContinuousDistribution {
/** 1 / 2(erfc^-1 (0.5))^2. Computed using Matlab's VPA to 30 digits. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogNormalDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogNormalDistribution.java
index 4f5681f..fb285d1 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogNormalDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogNormalDistribution.java
@@ -26,20 +26,15 @@ import org.apache.commons.rng.sampling.distribution.ZigguratSampler;
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Log-normal_distribution">log-normal distribution</a>.
*
- * <p>
- * <strong>Parameters:</strong>
- * {@code X} is log-normally distributed if its natural logarithm {@code log(X)}
- * is normally distributed. The probability distribution function of {@code X}
- * is given by (for {@code x > 0})
- * </p>
- * <p>
- * {@code exp(-0.5 * ((ln(x) - mu) / s)^2) / (s * sqrt(2 * pi) * x)}
- * </p>
- * <ul>
- * <li>{@code mu} is the mean of the normally distributed natural logarithm of this distribution,</li>
- * <li>{@code s} is standard deviation of the normally distributed natural logarithm of this
- * distribution.
- * </ul>
+ * <p>\( X \) is log-normally distributed if its natural logarithm \( \ln(x) \)
+ * is normally distributed. The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x; \mu, \sigma) = \frac 1 {x\sigma\sqrt{2\pi\,}} e^{-{\frac 1 2}\left( \frac{\ln x-\mu}{\sigma} \right)^2 } \]
+ *
+ * <p>for \( \mu \) the mean of the normally distributed natural logarithm of this distribution,
+ * \( \sigma > 0 \) the standard deviation of the normally distributed natural logarithm of this
+ * distribution, and
+ * \( x \in (0, \infty) \).
*/
public final class LogNormalDistribution extends AbstractContinuousDistribution {
/** 0.5 * ln(2 * pi). Computed to 25-digits precision. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogisticDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogisticDistribution.java
index 5ccd850..57332fe 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogisticDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/LogisticDistribution.java
@@ -18,6 +18,14 @@ package org.apache.commons.statistics.distribution;
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Logistic_distribution">logistic distribution</a>.
+ *
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x; \mu, s) = \frac{e^{-(x-\mu)/s}} {s\left(1+e^{-(x-\mu)/s}\right)^2} \]
+ *
+ * <p>for \( \mu \) the location,
+ * \( s > 0 \) the scale, and
+ * \( x \in (-\infty, \infty) \).
*/
public final class LogisticDistribution extends AbstractContinuousDistribution {
/** Support lower bound. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NakagamiDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NakagamiDistribution.java
index 6f32b9a..f8c64a5 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NakagamiDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NakagamiDistribution.java
@@ -22,6 +22,14 @@ import org.apache.commons.numbers.gamma.RegularizedGamma;
/**
* This class implements the <a href="http://en.wikipedia.org/wiki/Nakagami_distribution">Nakagami distribution</a>.
+ *
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x; \mu, \Omega) = \frac{2\mu^\mu}{\Gamma(\mu)\Omega^\mu}x^{2\mu-1}\exp\left(-\frac{\mu}{\Omega}x^2\right) \]
+ *
+ * <p>for \( \mu > 0 \) the shape,
+ * \( \Omega > 0 \) the scale, and
+ * \( x \in (0, \infty) \).
*/
public final class NakagamiDistribution extends AbstractContinuousDistribution {
/** Support lower bound. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NormalDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NormalDistribution.java
index 2848dd4..133d1fa 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NormalDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/NormalDistribution.java
@@ -26,6 +26,14 @@ import org.apache.commons.rng.sampling.distribution.ZigguratSampler;
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Normal_distribution">normal (Gaussian) distribution</a>.
+ *
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x; \mu, \sigma) = \frac 1 {\sigma\sqrt{2\pi}} e^{-{\frac 1 2}\left( \frac{x-\mu}{\sigma} \right)^2 } \]
+ *
+ * <p>for \( \mu \) the mean,
+ * \( \sigma > 0 \) the standard deviation, and
+ * \( x \in (-\infty, \infty) \).
*/
public final class NormalDistribution extends AbstractContinuousDistribution {
/** 0.5 * ln(2 * pi). Computed to 25-digits precision. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java
index c57b6a8..bc58ec7 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java
@@ -28,7 +28,9 @@ import org.apache.commons.rng.sampling.distribution.InverseTransformParetoSample
*
* <p>\[ f(x; k, \alpha) = \frac{\alpha k^\alpha}{x^{\alpha + 1}} \]
*
- * <p>for \( k > 0 \), \( \alpha > 0 \), \( x \in [k, \infty) \).
+ * <p>for \( k > 0 \),
+ * \( \alpha > 0 \), and
+ * \( x \in [k, \infty) \).
*
* <p>\( k \) is a <em>scale</em> parameter: this is the minimum possible value of \( X \).
* <br>\( \alpha \) is a <em>shape</em> parameter: this is the Pareto index.
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PascalDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PascalDistribution.java
index a66f363..40e31e5 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PascalDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/PascalDistribution.java
@@ -23,28 +23,38 @@ import org.apache.commons.numbers.gamma.RegularizedBeta;
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Negative_binomial_distribution">Pascal distribution.</a>
*
- * The Pascal distribution is a special case of the Negative Binomial distribution
+ * <p>The Pascal distribution is a special case of the Negative Binomial distribution
* where the number of successes parameter is an integer.
*
- * There are various ways to express the probability mass and distribution
+ * <p>There are various ways to express the probability mass and distribution
* functions for the Pascal distribution. The present implementation represents
- * the distribution of the number of failures before {@code r} successes occur.
+ * the distribution of the number of failures before \( r \) successes occur.
* This is the convention adopted in e.g.
* <a href="http://mathworld.wolfram.com/NegativeBinomialDistribution.html">MathWorld</a>,
* but <em>not</em> in
* <a href="http://en.wikipedia.org/wiki/Negative_binomial_distribution">Wikipedia</a>.
*
- * For a random variable {@code X} whose values are distributed according to this
- * distribution, the probability mass function is given by<br>
- * {@code P(X = k) = C(k + r - 1, r - 1) * p^r * (1 - p)^k,}<br>
- * where {@code r} is the number of successes, {@code p} is the probability of
- * success, and {@code X} is the total number of failures. {@code C(n, k)} is
- * the binomial coefficient ({@code n} choose {@code k}). The mean and variance
- * of {@code X} are<br>
- * {@code E(X) = (1 - p) * r / p, var(X) = (1 - p) * r / p^2.}<br>
- * Finally, the cumulative distribution function is given by<br>
- * {@code P(X <= k) = I(p, r, k + 1)},
- * where I is the regularized incomplete Beta function.
+ * <p>The probability mass function of \( X \) is:
+ *
+ * <p>\[ f(k; r, p) = \binom{k+r-1}{r-1} p^r \, (1-p)^k \]
+ *
+ * <p>for \( r \in \{1, 2, \dots\} \) the number of successes,
+ * \( p \in (0, 1] \) the probability of success,
+ * \( k \in \{0, 1, 2, \dots\} \) the total number of failures, and
+ *
+ * <p>\[ \binom{k+r-1}{r-1} = \frac{(k+r-1)!}{(r-1)! \, k!} \]
+ *
+ * <p>is the binomial coefficient.
+ *
+ * <p>The mean and variance of \( X \) are:
+ *
+ * <p>\[ \begin{aligned} \mathbb{E}(X) &= \frac {(1 - p) r}{p} \\ \mathrm{Var}(X) &= \frac {(1 - p) r}{p^2} \end{aligned} \]
+ *
+ * <p>The cumulative distribution function of \( X \) is:
+ *
+ * <p>\[ P(X \leq k) = I(p, r, k + 1) \]
+ *
+ * <p>where \( I \) is the regularized incomplete beta function.
*/
public final class PascalDistribution extends AbstractDiscreteDistribution {
/** The number of successes. */
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 f0c2295..85a2b1a 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
@@ -25,6 +25,13 @@ import org.apache.commons.rng.sampling.distribution.ZigguratSampler;
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Poisson_distribution">Poisson distribution</a>.
+ *
+ * <p>The probability mass function of \( X \) is:
+ *
+ * <p>\[ f(k; \lambda) = \frac{\lambda^k e^{-k}}{k!} \]
+ *
+ * <p>for \( \lambda \in (0, \infty) \) the mean and
+ * \( k \in \{0, 1, 2, \dots\} \) the number of events.
*/
public final class PoissonDistribution extends AbstractDiscreteDistribution {
/** 0.5 * ln(2 * pi). Computed to 25-digits precision. */
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 beecfa7..0eeb1e5 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
@@ -22,6 +22,14 @@ import org.apache.commons.numbers.gamma.LogGamma;
/**
* Implementation of <a href='http://en.wikipedia.org/wiki/Student's_t-distribution'>Student's t-distribution</a>.
+ *
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x; v) = \frac{\Gamma(\frac{\nu+1}{2})} {\sqrt{\nu\pi}\,\Gamma(\frac{\nu}{2})} \left(1+\frac{t^2}{\nu} \right)^{\!-\frac{\nu+1}{2}} \]
+ *
+ * <p>for \( v > 0 \) the degrees of freedom,
+ * \( \Gamma \) is the gamma function, and
+ * \( x \in (-\infty, \infty) \).
*/
public abstract class TDistribution extends AbstractContinuousDistribution {
/** A standard normal distribution used for calculations.
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 81ce547..baa18c2 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
@@ -18,7 +18,18 @@
package org.apache.commons.statistics.distribution;
/**
- * Implementation of the triangular real distribution.
+ * Implementation of the triangular distribution.
+ *
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x; a, b, c) = \begin{cases}
+ * \frac{2(x-a)}{(b-a)(c-a)} & \text{for } a \le x \lt c \\
+ * \frac{2}{b-a} & \text{for } x = c \\
+ * \frac{2(b-x)}{(b-a)(b-c)} & \text{for } c \lt x \le b \\
+ * \end{cases} \]
+ *
+ * <p>for \( -\infty \lt a \le c \le b \lt \infty \) and
+ * \( x \in [a, b] \).
*
* @see <a href="http://en.wikipedia.org/wiki/Triangular_distribution">
* Triangular distribution (Wikipedia)</a>
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TruncatedNormalDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TruncatedNormalDistribution.java
index 1dec468..d36fac6 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TruncatedNormalDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/TruncatedNormalDistribution.java
@@ -24,6 +24,17 @@ import org.apache.commons.numbers.gamma.Erfcx;
/**
* Implementation of the truncated normal distribution.
*
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x;\mu,\sigma,a,b) = \frac{1}{\sigma}\,\frac{\phi(\frac{x - \mu}{\sigma})}{\Phi(\frac{b - \mu}{\sigma}) - \Phi(\frac{a - \mu}{\sigma}) } \]
+ *
+ * <p>for \( \mu \) mean of the parent normal distribution,
+ * \( \sigma \) standard deviation of the parent normal distribution,
+ * \( -\infty \le a \lt b \le \infty \) the truncation interval, and
+ * \( x \in [a, b] \), where \( \phi \) is the probability
+ * density function of the standard normal distribution and \( \Phi \)
+ * is its cumulative distribution function.
+ *
* @see <a href="https://en.wikipedia.org/wiki/Truncated_normal_distribution">
* Truncated normal distribution (Wikipedia)</a>
*/
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformContinuousDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformContinuousDistribution.java
index d9acb29..d7fccf6 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformContinuousDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformContinuousDistribution.java
@@ -22,6 +22,13 @@ import org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler;
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Uniform_distribution_(continuous)">uniform distribution</a>.
+ *
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x; a, b) = \frac{1}{b-a} \]
+ *
+ * <p>for \( -\infty \lt a \lt b \lt \infty \) and
+ * \( x \in [a, b] \).
*/
public final class UniformContinuousDistribution extends AbstractContinuousDistribution {
/** Lower bound of this distribution (inclusive). */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformDiscreteDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformDiscreteDistribution.java
index dbfad35..5624324 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformDiscreteDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/UniformDiscreteDistribution.java
@@ -23,6 +23,13 @@ import org.apache.commons.rng.sampling.distribution.DiscreteUniformSampler;
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Uniform_distribution_(discrete)">
* uniform integer distribution</a>.
+ *
+ * <p>The probability mass function of \( X \) is:
+ *
+ * <p>\[ f(k; a, b) = \frac{1}{b-a+1} \]
+ *
+ * <p>for integer \( a, b \) and \( a \le b \) and
+ * \( k \in [a, b] \).
*/
public final class UniformDiscreteDistribution extends AbstractDiscreteDistribution {
/** Lower bound (inclusive) of this distribution. */
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/WeibullDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/WeibullDistribution.java
index a2de523..5ac33e7 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/WeibullDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/WeibullDistribution.java
@@ -22,15 +22,20 @@ import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.sampling.distribution.ZigguratSampler;
/**
- * Implementation of the Weibull distribution. This implementation uses the
- * two parameter form of the distribution defined by
- * <a href="http://mathworld.wolfram.com/WeibullDistribution.html">
- * Weibull Distribution</a>, equations (1) and (2).
+ * Implementation of the Weibull distribution.
+ *
+ * <p>The probability density function of \( X \) is:
+ *
+ * <p>\[ f(x;k,\lambda) = \frac{k}{\lambda}\left(\frac{x}{\lambda}\right)^{k-1}e^{-(x/\lambda)^{k}} \]
+ *
+ * <p>for \( k > 0 \) the shape,
+ * \( \lambda > 0 \) the scale, and
+ * \( x \in (0, \infty) \).
*
* <p>Note the special cases:
* <ul>
- * <li>{@code shape == 1} is the exponential distribution
- * <li>{@code shape == 2} is the Rayleigh distribution
+ * <li>\( k = 1 \) is the exponential distribution
+ * <li>\( k = 2 \) is the Rayleigh distribution with scale \( \sigma = \frac {\lambda}{\sqrt{2}} \)
* </ul>
*
* @see <a href="http://en.wikipedia.org/wiki/Weibull_distribution">Weibull distribution (Wikipedia)</a>
@@ -51,13 +56,13 @@ public final class WeibullDistribution extends AbstractContinuousDistribution {
private final double logShapeOverScale;
/**
- * @param alpha Shape parameter.
- * @param beta Scale parameter.
+ * @param shape Shape parameter.
+ * @param scale Scale parameter.
*/
- private WeibullDistribution(double alpha,
- double beta) {
- scale = beta;
- shape = alpha;
+ private WeibullDistribution(double shape,
+ double scale) {
+ this.scale = scale;
+ this.shape = shape;
shapeOverScale = shape / scale;
logShapeOverScale = Math.log(shapeOverScale);
}
@@ -65,22 +70,22 @@ public final class WeibullDistribution extends AbstractContinuousDistribution {
/**
* Creates a Weibull distribution.
*
- * @param alpha Shape parameter.
- * @param beta Scale parameter.
+ * @param shape Shape parameter.
+ * @param scale Scale parameter.
* @return the distribution
- * @throws IllegalArgumentException if {@code alpha <= 0} or {@code beta <= 0}.
+ * @throws IllegalArgumentException if {@code shape <= 0} or {@code scale <= 0}.
*/
- public static WeibullDistribution of(double alpha,
- double beta) {
- if (alpha <= 0) {
+ public static WeibullDistribution of(double shape,
+ double scale) {
+ if (shape <= 0) {
throw new DistributionException(DistributionException.NOT_STRICTLY_POSITIVE,
- alpha);
+ shape);
}
- if (beta <= 0) {
+ if (scale <= 0) {
throw new DistributionException(DistributionException.NOT_STRICTLY_POSITIVE,
- beta);
+ scale);
}
- return new WeibullDistribution(alpha, beta);
+ return new WeibullDistribution(shape, scale);
}
/**
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ZipfDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ZipfDistribution.java
index 1ca8b2d..0a2f26c 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ZipfDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ZipfDistribution.java
@@ -23,19 +23,17 @@ import org.apache.commons.rng.sampling.distribution.RejectionInversionZipfSample
/**
* Implementation of the <a href="https://en.wikipedia.org/wiki/Zipf's_law">Zipf distribution</a>.
- * <p>
- * <strong>Parameters:</strong>
- * For a random variable {@code X} whose values are distributed according to this
- * distribution, the probability mass function is given by:
- * <pre>
- * P(X = k) = H(N,s) * 1 / k^s for {@code k = 1,2,...,N}.
- * </pre>
- * <p>{@code H(N,s)} is the normalizing constant
- * which corresponds to the generalized harmonic number of order N of s.
- * <ul>
- * <li>{@code N} is the number of elements</li>
- * <li>{@code s} is the exponent</li>
- * </ul>
+ *
+ * <p>The probability mass function of \( X \) is:
+ *
+ * <p>\[ f(k; N, s) = \frac{1/k^s}{H_{N,s}} \]
+ *
+ * <p>for \( N \in \{1, 2, 3, \dots\} \) the number of elements,
+ * \( s \gt 0 \) the exponent characterizing the distribution,
+ * \( k \in \{1, 2, \dots, N\} \) the element rank, and
+ * \( H_{N,s} \) is the normalizing constant which corresponds to the
+ * <a href="https://en.wikipedia.org/wiki/Harmonic_number#Generalized_harmonic_numbers">
+ * generalized harmonic number</a> of order N of s.
*/
public final class ZipfDistribution extends AbstractDiscreteDistribution {
/** Number of elements. */
[commons-statistics] 04/05: Update javadoc for mean and variance
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 56b10747d553aeff6a8c7203851df0db4c8ff07d
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Fri Dec 17 20:31:25 2021 +0000
Update javadoc for mean and variance
Remove the statement 'or {@code Double.NaN} if it is not defined'.
This only applies to a few distributions. These distributions have been
updated to state they return NaN if the mean/variance is undefined.
This change prevents all distributions inheriting the javadoc and having
to override the return tag to state the mean/variance is finite.
---
.../commons/statistics/distribution/CauchyDistribution.java | 4 ++--
.../statistics/distribution/ContinuousDistribution.java | 4 ++--
.../commons/statistics/distribution/DiscreteDistribution.java | 4 ++--
.../apache/commons/statistics/distribution/FDistribution.java | 8 ++++++--
.../apache/commons/statistics/distribution/TDistribution.java | 10 +++++++---
5 files changed, 19 insertions(+), 11 deletions(-)
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java
index 33603e6..35f11e5 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/CauchyDistribution.java
@@ -156,7 +156,7 @@ public final class CauchyDistribution extends AbstractContinuousDistribution {
*
* <p>The mean is always undefined no matter the parameters.
*
- * @return mean (always Double.NaN)
+ * @return NaN
*/
@Override
public double getMean() {
@@ -168,7 +168,7 @@ public final class CauchyDistribution extends AbstractContinuousDistribution {
*
* <p>The variance is always undefined no matter the parameters.
*
- * @return variance (always Double.NaN)
+ * @return NaN
*/
@Override
public double getVariance() {
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ContinuousDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ContinuousDistribution.java
index 7391d2b..781fea5 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ContinuousDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ContinuousDistribution.java
@@ -138,14 +138,14 @@ public interface ContinuousDistribution {
/**
* Gets the mean of this distribution.
*
- * @return the mean, or {@code Double.NaN} if it is not defined.
+ * @return the mean.
*/
double getMean();
/**
* Gets the variance of this distribution.
*
- * @return the variance, or {@code Double.NaN} if it is not defined.
+ * @return the variance.
*/
double getVariance();
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/DiscreteDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/DiscreteDistribution.java
index a96ce86..6215ff4 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/DiscreteDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/DiscreteDistribution.java
@@ -155,14 +155,14 @@ public interface DiscreteDistribution {
/**
* Gets the mean of this distribution.
*
- * @return the mean, or {@code Double.NaN} if it is not defined.
+ * @return the mean.
*/
double getMean();
/**
* Gets the variance of this distribution.
*
- * @return the variance, or {@code Double.NaN} if it is not defined.
+ * @return the variance.
*/
double getVariance();
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java
index 1a39bd4..942ca90 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/FDistribution.java
@@ -211,8 +211,10 @@ public final class FDistribution extends AbstractContinuousDistribution {
* <p>For denominator degrees of freedom parameter {@code b}, the mean is
* <ul>
* <li>if {@code b > 2} then {@code b / (b - 2)},</li>
- * <li>else undefined ({@code Double.NaN}).
+ * <li>else undefined ({@code NaN}).
* </ul>
+ *
+ * @return the mean, or {@code NaN} if it is not defined.
*/
@Override
public double getMean() {
@@ -235,8 +237,10 @@ public final class FDistribution extends AbstractContinuousDistribution {
* if {@code b > 4} then
* {@code [2 * b^2 * (a + b - 2)] / [a * (b - 2)^2 * (b - 4)]},
* </li>
- * <li>else undefined ({@code Double.NaN}).
+ * <li>else undefined ({@code NaN}).
* </ul>
+ *
+ * @return the variance, or {@code NaN} if it is not defined.
*/
@Override
public double getVariance() {
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 d810509..299f18e 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
@@ -208,8 +208,10 @@ public abstract class TDistribution extends AbstractContinuousDistribution {
* <p>For degrees of freedom parameter {@code df}, the mean is
* <ul>
* <li>zero if {@code df > 1}, and</li>
- * <li>undefined ({@code Double.NaN}) otherwise.</li>
+ * <li>undefined ({@code NaN}) otherwise.</li>
* </ul>
+ *
+ * @return the mean, or {@code NaN} if it is not defined.
*/
@Override
public double getMean() {
@@ -222,9 +224,11 @@ public abstract class TDistribution extends AbstractContinuousDistribution {
* <p>For degrees of freedom parameter {@code df}, the variance is
* <ul>
* <li>{@code df / (df - 2)} if {@code df > 2},</li>
- * <li>infinite ({@code Double.POSITIVE_INFINITY}) if {@code 1 < df <= 2}, and</li>
- * <li>undefined ({@code Double.NaN}) otherwise.</li>
+ * <li>positive infinity if {@code 1 < df <= 2}, and</li>
+ * <li>undefined ({@code NaN}) otherwise.</li>
* </ul>
+ *
+ * @return the mean, or {@code NaN} if it is not defined.
*/
@Override
public double getVariance() {