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Changed getN() to return long. Changed evalutate() to return NaN if sample size is less than 3 (consistent w/ getResult()). 

git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@141367 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Phil Steitz 2004-07-10 17:02:43 +00:00
parent 9360c37834
commit 5895dba6f5
1 changed files with 28 additions and 34 deletions
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62
src/java/org/apache/commons/math/stat/univariate/moment/Skewness.java
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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: 1.24 $ $Date: 2004/07/04 09:02:36 $
* @version $Revision: 1.25 $ $Date: 2004/07/10 17:02:43 $
*/
public class Skewness extends AbstractStorelessUnivariateStatistic implements Serializable {
@ -104,7 +104,7 @@ public class Skewness extends AbstractStorelessUnivariateStatistic implements Se
/**
* @see org.apache.commons.math.stat.univariate.StorelessUnivariateStatistic#getN()
*/
public double getN() {
public long getN() {
return moment.getN();
}
@ -139,41 +139,35 @@ public class Skewness extends AbstractStorelessUnivariateStatistic implements Se
// Initialize the skewness
double skew = Double.NaN;
if (test(values, begin, length)) {
if (test(values, begin, length) && length > 2 ){
Mean mean = new Mean();
if (length <= 2) {
skew = 0.0;
} else {
// Get the mean and the standard deviation
double m = mean.evaluate(values, begin, length);
// Calc the std, this is implemented here instead
// of using the standardDeviation method eliminate
// a duplicate pass to get the mean
double accum = 0.0;
double accum2 = 0.0;
for (int i = begin; i < begin + length; i++) {
accum += Math.pow((values[i] - m), 2.0);
accum2 += (values[i] - m);
}
double stdDev = Math.sqrt((accum - (Math.pow(accum2, 2) / ((double) length))) /
(double) (length - 1));
double accum3 = 0.0;
for (int i = begin; i < begin + length; i++) {
accum3 += Math.pow(values[i] - m, 3.0d);
}
accum3 /= Math.pow(stdDev, 3.0d);
// Get N
double n0 = length;
// Calculate skewness
skew = (n0 / ((n0 - 1) * (n0 - 2))) * accum3;
// Get the mean and the standard deviation
double m = mean.evaluate(values, begin, length);
// Calc the std, this is implemented here instead
// of using the standardDeviation method eliminate
// a duplicate pass to get the mean
double accum = 0.0;
double accum2 = 0.0;
for (int i = begin; i < begin + length; i++) {
accum += Math.pow((values[i] - m), 2.0);
accum2 += (values[i] - m);
}
double stdDev = Math.sqrt((accum - (Math.pow(accum2, 2) / ((double) length))) /
(double) (length - 1));
double accum3 = 0.0;
for (int i = begin; i < begin + length; i++) {
accum3 += Math.pow(values[i] - m, 3.0d);
}
accum3 /= Math.pow(stdDev, 3.0d);
// Get N
double n0 = length;
// Calculate skewness
skew = (n0 / ((n0 - 1) * (n0 - 2))) * accum3;
}
return skew;
}
}