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Fix javadoc issues

This commit is contained in:
Ray DeCampo 2017-05-12 17:52:09 -04:00
parent 6440b7f648
commit 53d9d652f2
5 changed files with 7 additions and 7 deletions
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2
src/main/java/org/apache/commons/math4/stat/descriptive/moment/GeometricMean.java
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@ -35,7 +35,7 @@ import org.apache.commons.math4.util.MathUtils;
* Uses a {@link SumOfLogs} instance to compute sum of logs and returns * Uses a {@link SumOfLogs} instance to compute sum of logs and returns
* <code> exp( 1/n (sum of logs) ).</code> Therefore, </p> * <code> exp( 1/n (sum of logs) ).</code> Therefore, </p>
* <ul> * <ul>
* <li>If any of values are < 0, the result is <code>NaN.</code></li> * <li>If any of values are {@code < 0}, the result is <code>NaN.</code></li>
* <li>If all values are non-negative and less than * <li>If all values are non-negative and less than
* <code>Double.POSITIVE_INFINITY</code>, but at least one value is 0, the * <code>Double.POSITIVE_INFINITY</code>, but at least one value is 0, the
* result is <code>0.</code></li> * result is <code>0.</code></li>

2
src/main/java/org/apache/commons/math4/stat/descriptive/moment/Kurtosis.java
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@ -36,7 +36,7 @@ import org.apache.commons.math4.util.MathUtils;
* where n is the number of values, mean is the {@link Mean} and std is the * where n is the number of values, mean is the {@link Mean} and std is the
* {@link StandardDeviation}</p> * {@link StandardDeviation}</p>
* <p> * <p>
* Note that this statistic is undefined for n < 4. <code>Double.Nan</code> * Note that this statistic is undefined for {@code n < 4}. <code>Double.Nan</code>
* is returned when there is not sufficient data to compute the statistic. * is returned when there is not sufficient data to compute the statistic.
* Note that Double.NaN may also be returned if the input includes NaN * Note that Double.NaN may also be returned if the input includes NaN
* and / or infinite values.</p> * and / or infinite values.</p>

2
src/main/java/org/apache/commons/math4/stat/descriptive/moment/SemiVariance.java
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@ -30,7 +30,7 @@ import org.apache.commons.math4.util.MathUtils;
* We define the <i>downside semivariance</i> of a set of values <code>x</code> * We define the <i>downside semivariance</i> of a set of values <code>x</code>
* against the <i>cutoff value</i> <code>cutoff</code> to be <br> * against the <i>cutoff value</i> <code>cutoff</code> to be <br>
* <code>&Sigma; (x[i] - target)<sup>2</sup> / df</code> <br> * <code>&Sigma; (x[i] - target)<sup>2</sup> / df</code> <br>
* where the sum is taken over all <code>i</code> such that <code>x[i] < cutoff</code> * where the sum is taken over all <code>i</code> such that {@code x[i] < cutoff}
* and <code>df</code> is the length of <code>x</code> (non-bias-corrected) or * and <code>df</code> is the length of <code>x</code> (non-bias-corrected) or
* one less than this number (bias corrected). The <i>upside semivariance</i> * one less than this number (bias corrected). The <i>upside semivariance</i>
* is defined similarly, with the sum taken over values of <code>x</code> that * is defined similarly, with the sum taken over values of <code>x</code> that

2
src/main/java/org/apache/commons/math4/stat/descriptive/moment/Skewness.java
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@ -35,7 +35,7 @@ import org.apache.commons.math4.util.MathUtils;
* where n is the number of values, mean is the {@link Mean} and std is the * where n is the number of values, mean is the {@link Mean} and std is the
* {@link StandardDeviation} </p> * {@link StandardDeviation} </p>
* <p> * <p>
* Note that this statistic is undefined for n < 3. <code>Double.Nan</code> * Note that this statistic is undefined for {@code n < 3}. <code>Double.Nan</code>
* is returned when there is not sufficient data to compute the statistic. * is returned when there is not sufficient data to compute the statistic.
* Double.NaN may also be returned if the input includes NaN and / or * Double.NaN may also be returned if the input includes NaN and / or
* infinite values.</p> * infinite values.</p>

6
src/main/java/org/apache/commons/math4/stat/descriptive/moment/Variance.java
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@ -276,10 +276,10 @@ public class Variance extends AbstractStorelessUnivariateStatistic implements Se
* the input array, or <code>Double.NaN</code> if the designated subarray * the input array, or <code>Double.NaN</code> if the designated subarray
* is empty.</p> * is empty.</p>
* <p> * <p>
* Uses the formula <pre> * Uses the formula <div style="white-space: pre"><code>
* &Sigma;(weights[i]*(values[i] - weightedMean)<sup>2</sup>)/(&Sigma;(weights[i]) - 1) * &Sigma;(weights[i]*(values[i] - weightedMean)<sup>2</sup>)/(&Sigma;(weights[i]) - 1)
* </pre> * </code></div>
* where weightedMean is the weighted mean</p> * where weightedMean is the weighted mean
* <p> * <p>
* This formula will not return the same result as the unweighted variance when all * This formula will not return the same result as the unweighted variance when all
* weights are equal, unless all weights are equal to 1. The formula assumes that * weights are equal, unless all weights are equal to 1. The formula assumes that