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Posted to commits@commons.apache.org by ah...@apache.org on 2022/11/21 19:23:18 UTC
[commons-statistics] 05/12: Use MathJax for mean and variance javadoc
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 25abd2aa5924b0282900c139011e919975c0a062
Author: Alex Herbert <ah...@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, \( \sigma > 0 \) 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, \( \sigma > 0 \) 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() {