pal.statistics
Class DiscreteStatistics

java.lang.Object
  pal.statistics.DiscreteStatistics

public class DiscreteStatistics
extends java.lang.Object

simple discrete statistics (mean, variance, cumulative probability, quantiles etc.)

Version:

$Id: DiscreteStatistics.java,v 1.5 2001/07/13 14:39:13 korbinian Exp $

Author:

Korbinian Strimmer

Constructor Summary

DiscreteStatistics()

Method Summary

static double	cdf(double z, double[] x) compute the cumulative probability Pr(x <= z) for a given z and a distribution of x
static double	cdf(double z, double[] x, int[] indices) compute the cumulative probability Pr(x <= z) for a given z and a distribution of x
static double	mean(double[] x) compute mean
static double	quantile(double q, double[] x) compute the q-th quantile for a distribution of x (= inverse cdf)
static double	quantile(double q, double[] x, int[] indices) compute the q-th quantile for a distribution of x (= inverse cdf)
static double	skewness(double[] x) compute fisher skewness
static double	stdev(double[] x) compute standard deviation
static double	variance(double[] x) compute variance (ML estimator)
static double	variance(double[] x, double mean) compute variance (ML estimator)
static double	varianceSampleMean(double[] x) compute variance of sample mean (ML estimator)
static double	varianceSampleMean(double[] x, double mean) compute variance of sample mean (ML estimator)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

DiscreteStatistics

public DiscreteStatistics()

Method Detail

mean

public static double mean(double[] x)

compute mean

Parameters:

x - list of numbers

Returns:

mean

variance

public static double variance(double[] x,
                              double mean)

compute variance (ML estimator)

Parameters:

x - list of numbers

mean - assumed mean of x

Returns:

variance of x (ML estimator)

skewness

public static double skewness(double[] x)

compute fisher skewness

Parameters:

x - list of numbers

Returns:

skewness of x

stdev

public static double stdev(double[] x)

compute standard deviation

Parameters:

x - list of numbers

Returns:

standard deviation of x

variance

public static double variance(double[] x)

compute variance (ML estimator)

Parameters:

x - list of numbers

Returns:

variance of x (ML estimator)

varianceSampleMean

public static double varianceSampleMean(double[] x,
                                        double mean)

compute variance of sample mean (ML estimator)

Parameters:

x - list of numbers

mean - assumed mean of x

Returns:

variance of x (ML estimator)

varianceSampleMean

public static double varianceSampleMean(double[] x)

compute variance of sample mean (ML estimator)

Parameters:

x - list of numbers

Returns:

variance of x (ML estimator)

quantile

public static double quantile(double q,
                              double[] x,
                              int[] indices)

compute the q-th quantile for a distribution of x (= inverse cdf)

Parameters:

q - quantile (0 < q <= 1)

x - discrete distribution (an unordered list of numbers)

indices - index sorting x

Returns:

q-th quantile

quantile

public static double quantile(double q,
                              double[] x)

compute the q-th quantile for a distribution of x (= inverse cdf)

Parameters:

q - quantile (0 <= q <= 1)

x - discrete distribution (an unordered list of numbers)

Returns:

q-th quantile

cdf

public static double cdf(double z,
                         double[] x,
                         int[] indices)

compute the cumulative probability Pr(x <= z) for a given z and a distribution of x

Parameters:

z - threshold value

x - discrete distribution (an unordered list of numbers)

indices - index sorting x

Returns:

cumulative probability

cdf

public static double cdf(double z,
                         double[] x)

compute the cumulative probability Pr(x <= z) for a given z and a distribution of x

Parameters:

z - threshold value

x - discrete distribution (an unordered list of numbers)

Returns:

cumulative probability