Catalano.Statistics.Distributions

Class ChiSquareDistribution

java.lang.Object

Catalano.Statistics.Distributions.ChiSquareDistribution

All Implemented Interfaces:

IDistribution

public class ChiSquareDistribution
extends java.lang.Object
implements IDistribution

Chi-Square (χ²) probability distribution. In probability theory and statistics, the chi-square distribution (also chi-squared or χ²-distribution) with k degrees of freedom is the distribution of a sum of the squares of k independent standard normal random variables. It is one of the most widely used probability distributions in inferential statistics, e.g. in hypothesis testing, or in construction of confidence intervals.

Constructor Summary

Constructors

Constructor and Description
ChiSquareDistribution(int degreesOfFreedom)

Method Summary

Modifier and Type	Method and Description
double	ComplementaryDistributionFunction(double x)
double	DistributionFunction(double x) Gets the cumulative distribution function (cdf) for this distribution evaluated at point x.
double	Entropy() Gets the entropy for this distribution.
int	getDegreesOfFreedom()
double	LogProbabilityDensityFunction(double x) Gets the log-probability density function (pdf) for this distribution evaluated at point x.
double	Mean() Gets the mean for this distribution.
double	ProbabilityDensityFunction(double x) Gets the probability density function (pdf) for this distribution evaluated at point x.
double	Variance() Gets the variance for this distribution.

Methods inherited from class java.lang.Object

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

Constructor Detail

ChiSquareDistribution

public ChiSquareDistribution(int degreesOfFreedom)

Method Detail

getDegreesOfFreedom

public int getDegreesOfFreedom()

Mean

public double Mean()

Description copied from interface: IDistribution

Gets the mean for this distribution.

Specified by:

Mean in interface IDistribution

Returns:

The distribution's mean value.

Variance

public double Variance()

Description copied from interface: IDistribution

Gets the variance for this distribution.

Specified by:

Variance in interface IDistribution

Returns:

The distribution's variance.

Entropy

public double Entropy()

Description copied from interface: IDistribution

Gets the entropy for this distribution.

Specified by:

Entropy in interface IDistribution

Returns:

The distribution's entropy.

ComplementaryDistributionFunction

public double ComplementaryDistributionFunction(double x)

DistributionFunction

public double DistributionFunction(double x)

Description copied from interface: IDistribution

Gets the cumulative distribution function (cdf) for this distribution evaluated at point x.
The Cumulative Distribution Function (CDF) describes the cumulative probability that a given value or any value smaller than it will occur.

Specified by:

DistributionFunction in interface IDistribution

Parameters:

x - A single point in the distribution range.

Returns:

The probability of x occurring in the current distribution.

ProbabilityDensityFunction

public double ProbabilityDensityFunction(double x)

Description copied from interface: IDistribution

Gets the probability density function (pdf) for this distribution evaluated at point x.
The Probability Density Function (PDF) describes the probability that a given value x will occur.

Specified by:

ProbabilityDensityFunction in interface IDistribution

Parameters:

x - A single point in the distribution range.

Returns:

The probability of x occurring in the current distribution.

LogProbabilityDensityFunction

public double LogProbabilityDensityFunction(double x)

Description copied from interface: IDistribution

Gets the log-probability density function (pdf) for this distribution evaluated at point x.
The Probability Density Function (PDF) describes the probability that a given value x will occur.

Specified by:

LogProbabilityDensityFunction in interface IDistribution

Parameters:

x - A single point in the distribution range.

Returns:

The probability of x occurring in the current distribution.