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Corrected javadoc, minor improvment to computation. 

git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@141131 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Phil Steitz 2004-03-20 23:55:19 +00:00
parent 4b4b6aed43
commit f5ae32413a
1 changed files with 19 additions and 18 deletions
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37
src/java/org/apache/commons/math/stat/univariate/moment/Skewness.java
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@ -20,7 +20,15 @@ import java.io.Serializable;
import org.apache.commons.math.stat.univariate.AbstractStorelessUnivariateStatistic;
/**
* @version $Revision: 1.17 $ $Date: 2004/03/04 04:25:09 $
* Computes Skewness.
* <p>
* We use the following formula to define skewness:
* <p>
* skewness = [n / (n -1) (n - 2)] sum[(x_i - mean)^3] / std^3
* <p>
* where n is the number of values, mean is the {@link Mean} and std is the {@link StandardDeviation}
*
* @version $Revision: 1.18 $ $Date: 2004/03/20 23:55:19 $
*/
public class Skewness extends AbstractStorelessUnivariateStatistic implements Serializable {
@ -64,7 +72,9 @@ public class Skewness extends AbstractStorelessUnivariateStatistic implements Se
}
/**
* @see org.apache.commons.math.stat.univariate.StorelessUnivariateStatistic#getResult()
* Returns the value of the statistic based on the values that have been added.
* <p>
* See {@link Skewness} for the definition used in the computation.
*/
public double getResult() {
if (n < moment.n) {
@ -110,16 +120,10 @@ public class Skewness extends AbstractStorelessUnivariateStatistic implements Se
Mean mean = new Mean();
/**
* Returns the skewness of a collection of values. Skewness is a
* measure of the assymetry of a given distribution.
* This algorithm uses a corrected two pass algorithm of the following
* <a href="http://lib-www.lanl.gov/numerical/bookcpdf/c14-1.pdf">
* corrected two pass formula (14.1.8)</a>, and also referenced in
* Returns the Skewness of the values array.
* <p>
* "Algorithms for Computing the Sample Variance: Analysis and
* Recommendations", Chan, T.F., Golub, G.H., and LeVeque, R.J.
* 1983, American Statistician, vol. 37, pp. 242?247.
* </p>
* See {@link Skewness} for the definition used in the computation.
*
* @param values Is a double[] containing the values
* @param begin processing at this point in the array
* @param length the number of elements to include
@ -151,17 +155,14 @@ public class Skewness extends AbstractStorelessUnivariateStatistic implements Se
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 stdDev = Math.sqrt((accum - (Math.pow(accum2, 2) / ((double) length))) /
(double) (length - 1));
// Calculate the skew as the sum the cubes of the distance
// from the mean divided by the standard deviation.
double accum3 = 0.0;
for (int i = begin; i < begin + length; i++) {
accum3 += Math.pow((values[i] - m) / stdDev, 3.0);
accum3 += Math.pow(values[i] - m, 3.0d);
}
accum3 /= Math.pow(stdDev, 3.0d);
// Get N
double n0 = length;