javadoc only.

git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@141376 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Phil Steitz 2004-07-11 18:39:08 +00:00
parent e3c0133202
commit 96fc8f14c4
3 changed files with 12 additions and 9 deletions

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@ -34,7 +34,7 @@ import org.apache.commons.math.stat.univariate.AbstractStorelessUnivariateStatis
* one of the threads invokes the <code>increment()</code> or
* <code>clear()</code> method, it must be synchronized externally.
*
* @version $Revision: 1.20 $ $Date: 2004/07/10 17:09:08 $
* @version $Revision: 1.21 $ $Date: 2004/07/11 18:39:08 $
*/
public class Max extends AbstractStorelessUnivariateStatistic implements Serializable {
@ -97,7 +97,7 @@ public class Max extends AbstractStorelessUnivariateStatistic implements Seriali
* @param values the input array
* @param begin index of the first array element to include
* @param length the number of elements to include
* @return the mean of the values or Double.NaN if length = 0
* @return the maximum of the values or Double.NaN if length = 0
* @throws IllegalArgumentException if the array is null or the array index
* parameters are not valid
*/

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@ -34,7 +34,7 @@ import org.apache.commons.math.stat.univariate.AbstractStorelessUnivariateStatis
* one of the threads invokes the <code>increment()</code> or
* <code>clear()</code> method, it must be synchronized externally.
*
* @version $Revision: 1.21 $ $Date: 2004/07/10 17:09:08 $
* @version $Revision: 1.22 $ $Date: 2004/07/11 18:39:08 $
*/
public class Min extends AbstractStorelessUnivariateStatistic implements Serializable {
@ -97,7 +97,7 @@ public class Min extends AbstractStorelessUnivariateStatistic implements Seriali
* @param values the input array
* @param begin index of the first array element to include
* @param length the number of elements to include
* @return the mean of the values or Double.NaN if length = 0
* @return the minimum of the values or Double.NaN if length = 0
* @throws IllegalArgumentException if the array is null or the array index
* parameters are not valid
*/

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@ -60,7 +60,7 @@ import org.apache.commons.math.stat.univariate.AbstractUnivariateStatistic;
* one of the threads invokes the <code>increment()</code> or
* <code>clear()</code> method, it must be synchronized externally.
*
* @version $Revision: 1.22 $ $Date: 2004/07/04 09:02:36 $
* @version $Revision: 1.23 $ $Date: 2004/07/11 18:39:08 $
*/
public class Percentile extends AbstractUnivariateStatistic implements Serializable {
@ -102,7 +102,8 @@ public class Percentile extends AbstractUnivariateStatistic implements Serializa
* <li>Returns (for any value of <code>p</code>) <code>values[0]</code>
* if <code>values</code> has length <code>1</code></li>
* <li>Throws <code>IllegalArgumentException</code> if <code>values</code>
* is null </li>
* is null or p is not a valid quantile value (p must be greater than 0
* and less than or equal to 100) </li>
* </ul>
* <p>
* See {@link Percentile} for a description of the percentile estimation
@ -110,8 +111,9 @@ public class Percentile extends AbstractUnivariateStatistic implements Serializa
*
* @param values input array of values
* @param p the percentile value to compute
* @return the result of the evaluation or Double.NaN if the array is empty
* @throws IllegalArgumentException if <code>values</code> is null
* @return the percentile value or Double.NaN if the array is empty
* @throws IllegalArgumentException if <code>values</code> is null
* or p is invalid
*/
public double evaluate(final double[] values, final double p) {
test(values, 0, 0);
@ -161,7 +163,8 @@ public class Percentile extends AbstractUnivariateStatistic implements Serializa
* if <code>length = 1 </code></li>
* <li>Throws <code>IllegalArgumentException</code> if <code>values</code>
* is null , <code>begin</code> or <code>length</code> is invalid, or
* <code>p</code> is not a valid quantile value</li>
* <code>p</code> is not a valid quantile value (p must be greater than 0
* and less than or equal to 100)</li>
* </ul>
* <p>
* See {@link Percentile} for a description of the percentile estimation