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/*
* Statistics
*
* Copyright (c) 2003 Marco Schmidt.
* All rights reserved.
*/
package net.sourceforge.jiu.util;
/**
* A number of static methods to compute statistical properties of an
* array of double values.
* Implements the computation of mean, variance and standard deviation
* for <code>double</code> values.
* @author Marco Schmidt
* @since 0.11.0
*/
public class Statistics
{
private Statistics()
{
}
/**
* Computes the mean value for the argument array.
* Adds all values and divides them by the number of array elements.
* @param values double array on which the mean is to be determined
* @return computed mean value
* @throws IllegalArgumentException if the array has not at least one element
*/
public static double computeMean(double[] values)
{
return computeMean(values, 0, values.length);
}
/**
* Computes the mean value for some elements of the argument array.
* Adds all values and divides them by the number of array elements.
* @param values array from which elements are read
* @param offset index of the first element to be used
* @param number number of elements to be used
* @return computed mean value
* @throws IllegalArgumentException if the array has not at least one element
*/
public static double computeMean(double[] values, int offset, int number)
{
if (number < 1)
{
throw new IllegalArgumentException("The number of values to process must be one or larger.");
}
double sum = 0;
final int UNTIL = offset + number;
do
{
sum += values[offset++];
}
while (offset != UNTIL);
return sum / number;
}
/**
* Computes the standard deviation for the argument array of values.
* @param values array from which elements are read
* @return computed standard deviation
* @throws IllegalArgumentException if the array has not at least two elements
*/
public static double computeStandardDeviation(double[] values)
{
return computeStandardDeviation(values, 0, values.length);
}
/**
* Computes the standard deviation for the argument array of values.
* Reuses the mean value for that argument which must have been computed before.
* @param values array from which elements are read
* @param mean the mean value for the array, possibly computed with a
* call to {@link #computeMean(double[])}.
* @return computed standard deviation
* @throws IllegalArgumentException if the array has not at least two elements
*/
public static double computeStandardDeviation(double[] values, double mean)
{
return computeStandardDeviation(values, 0, values.length, mean);
}
/**
* Computes the standard deviation for some of the argument array's values.
* If you already have computed a mean value using {@link #computeMean(double[], int, int)},
* better call {@link #computeStandardDeviation(double[], int, int, double)}.
* Otherwise, this method has to compute mean again.
* @param values array from which elements are read
* @param offset first element to be used
* @param number number of elements used starting at values[offset]
* @return computed standard deviation
* @throws IllegalArgumentException if the array has not at least two elements
*/
public static double computeStandardDeviation(double[] values, int offset, int number)
{
double mean = computeMean(values, offset, number);
return computeStandardDeviation(values, 0, values.length, mean);
}
/**
* Computes the standard deviation for some of the argument array's values.
* Use this version of the method if you already have a mean value,
* otherwise this method must be computed again.
* @param values array from which elements are read
* @param offset first element to be used
* @param number number of elements used starting at values[offset]
* @param mean value of the elements
* @return computed standard deviation
* @throws IllegalArgumentException if the array has not at least two elements
*/
public static double computeStandardDeviation(double[] values, int offset, int number, double mean)
{
return Math.sqrt(computeVariance(values, offset, number, mean));
}
/**
* Computes the variance for the argument array.
* @param values array from which elements are read
* @return variance for the array elements
* @throws IllegalArgumentException if the array has not at least two elements
*/
public static double computeVariance(final double[] values)
{
return computeVariance(values, 0, values.length);
}
/**
* Computes the variance for some of the argument array's values.
* @param values array from which elements are read
* @param mean the mean for the array elements
* @return variance for the array elements
* @throws IllegalArgumentException if the array has not at least two elements
*/
public static double computeVariance(final double[] values, final double mean)
{
return computeVariance(values, 0, values.length, mean);
}
/**
* Computes the variance for some of the argument array's values.
* If you already have computed a mean value using {@link #computeMean(double[], int, int)},
* better call {@link #computeVariance(double[], int, int, double)}.
* Otherwise, this method has to compute mean again.
* @param values array from which elements are read
* @param offset first element to be used
* @param number number of elements used starting at values[offset]
* @return computed variance
* @throws IllegalArgumentException if the array has not at least two elements
*/
public static double computeVariance(final double[] values, int offset, final int number)
{
double mean = computeMean(values, offset, number);
return computeVariance(values, 0, values.length, mean);
}
/**
* Computes the variance for some of the argument array's values.
* Use this version of the method in case mean has already been
* computed.
* @param values array from which elements are read
* @param offset first element to be used
* @param number number of elements used starting at values[offset]
* @param mean the mean for the array elements
* @return computed variance
* @throws IllegalArgumentException if the array has not at least two elements
*/
public static double computeVariance(final double[] values, int offset, final int number, final double mean)
{
if (number < 2)
{
throw new IllegalArgumentException("The number of values to process must be two or larger.");
}
double sum = 0;
final int UNTIL = offset + number;
do
{
double diff = values[offset++] - mean;
sum += diff * diff;
}
while (offset != UNTIL);
return sum / (number - 1);
}
}
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