[commons-statistics] 05/12: Use MathJax for mean and variance javadoc

[aherbert]

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

commit 25abd2aa5924b0282900c139011e919975c0a062
Author: Alex Herbert <aherb...@apache.org>
AuthorDate: Mon Nov 21 18:42:15 2022 +0000

    Use MathJax for mean and variance javadoc
---
 .../statistics/distribution/LogNormalDistribution.java       | 12 ++++++++----
 1 file changed, 8 insertions(+), 4 deletions(-)

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 686aa03..b466f58 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
@@ -211,8 +211,10 @@ public final class LogNormalDistribution extends 
AbstractContinuousDistribution
     /**
      * {@inheritDoc}
      *
-     * <p>For {@code mu} and sigma {@code s}, the mean is
-     * {@code exp(m + s^2 / 2)}.
+     * <p>For \( \mu \) the mean of the normally distributed natural logarithm 
of
+     * this distribution, \( \sigma &gt; 0 \) the standard deviation of the 
normally
+     * distributed natural logarithm of this distribution, the mean is
+     * \( \exp(\mu + \frac{\sigma^2}{2}) \).
      */
     @Override
     public double getMean() {
@@ -223,8 +225,10 @@ public final class LogNormalDistribution extends 
AbstractContinuousDistribution
     /**
      * {@inheritDoc}
      *
-     * <p>For {@code mu} and sigma {@code s}, the variance is
-     * {@code (exp(s^2) - 1) * exp(2 * m + s^2)}.
+     * <p>For \( \mu \) the mean of the normally distributed natural logarithm 
of
+     * this distribution, \( \sigma &gt; 0 \) the standard deviation of the 
normally
+     * distributed natural logarithm of this distribution, the variance is
+     * \( [\exp(\sigma^2) - 1)]  \exp(2 \mu + \sigma^2) \).
      */
     @Override
     public double getVariance() {