ibspan.tss.um.statistics
Class StatisticCalculator

java.lang.Object
  ibspan.tss.um.statistics.StatisticCalculator

public class StatisticCalculator
extends Object

Calculator for simple statistic operations.

Author:

Maciej Gawinecki

Constructor Summary

StatisticCalculator()

Method Summary

static double	binomialMean(double p, double n) Computes mean value for binomial distribution.
static double	binomialStdDev(double p, double n) Computes standard deviation for binomial distribution.
static double	expectedValue(double[] population) Calculates expected value for distribution with given sample population.
static double	normalQuantile(double prob) Compute Z statistic for normal distribution.
static double	quantile(int q, int k, double[] population) Estimating of k-th q-quantile based on empirical distribution function with averaging.
static double	sigmoid(double x, double a) Computes sigmoid function for the given argument

Methods inherited from class java.lang.Object

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

Constructor Detail

StatisticCalculator

public StatisticCalculator()

Method Detail

normalQuantile

public static double normalQuantile(double prob)

Compute Z statistic for normal distribution.

Parameters:

prob -

Returns:

binomialMean

public static double binomialMean(double p,
                                  double n)

Computes mean value for binomial distribution.

Parameters:

p - probability of success

n - number of success

Returns:

mean value

binomialStdDev

public static double binomialStdDev(double p,
                                    double n)

Computes standard deviation for binomial distribution.

Parameters:

p - probability of success

n - number of probes

Returns:

standandar deviation

sigmoid

public static double sigmoid(double x,
                             double a)

Computes sigmoid function for the given argument

Parameters:

x - argument

a - 'a' parameter

Returns:

value of the function

quantile

public static double quantile(int q,
                              int k,
                              double[] population)

Estimating of k-th q-quantile based on empirical distribution function with averaging. Detailed equations can be found here.

Parameters:

q - is order of quantile

k - is number of quantile

population - sample population sorted ascendingly

Returns:

value of k-th q-quantile from the given population

expectedValue

public static double expectedValue(double[] population)

Calculates expected value for distribution with given sample population. In fact this is average, since each individual in population has the same probability.

Parameters:

population - is sample population

Returns:

exptected value