Made assumption about precomputed mean explicit in javadoc. Added missing method.
git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@141437 13f79535-47bb-0310-9956-ffa450edef68
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@ -30,7 +30,7 @@ import org.apache.commons.math.stat.univariate.AbstractStorelessUnivariateStatis
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* one of the threads invokes the <code>increment()</code> or
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* <code>clear()</code> method, it must be synchronized externally.
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*
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* @version $Revision: 1.22 $ $Date: 2004/07/18 04:42:02 $
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* @version $Revision: 1.23 $ $Date: 2004/09/01 15:54:39 $
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*/
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public class StandardDeviation extends AbstractStorelessUnivariateStatistic
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implements Serializable {
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@ -133,6 +133,11 @@ public class StandardDeviation extends AbstractStorelessUnivariateStatistic
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* <p>
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* Returns 0 for a single-value (i.e. length = 1) sample.
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* <p>
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* The formula used assumes that the supplied mean value is the arithmetic
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* mean of the sample data, not a known population parameter. This method
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* is supplied only to save computation when the mean has already been
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* computed.
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* <p>
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* Throws <code>IllegalArgumentException</code> if the array is null.
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* <p>
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* Does not change the internal state of the statistic.
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@ -149,4 +154,30 @@ public class StandardDeviation extends AbstractStorelessUnivariateStatistic
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final int begin, final int length) {
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return Math.sqrt(variance.evaluate(values, mean, begin, length));
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}
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/**
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* Returns the Standard Deviation of the entries in the input array, using
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* the precomputed mean value. Returns
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* <code>Double.NaN</code> if the designated subarray is empty.
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* <p>
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* Returns 0 for a single-value (i.e. length = 1) sample.
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* <p>
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* The formula used assumes that the supplied mean value is the arithmetic
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* mean of the sample data, not a known population parameter. This method
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* is supplied only to save computation when the mean has already been
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* computed.
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* <p>
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* Throws <code>IllegalArgumentException</code> if the array is null.
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* <p>
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* Does not change the internal state of the statistic.
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*
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* @param values the input array
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* @param mean the precomputed mean value
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* @return the standard deviation of the values or Double.NaN if length = 0
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* @throws IllegalArgumentException if the array is null or the array index
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* parameters are not valid
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*/
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public double evaluate(final double[] values, final double mean) {
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return Math.sqrt(variance.evaluate(values, mean));
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}
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}
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