com.mockturtlesolutions.snifflib.stats

Class GammaDistribution

java.lang.Object

com.mockturtlesolutions.snifflib.stats.ProbabilityDensity

com.mockturtlesolutions.snifflib.stats.GammaDistribution

All Implemented Interfaces:

NamedParameters, OptimizableScalar, CDF, InvCDF

public class GammaDistribution
extends ProbabilityDensity

Field Summary

Fields inherited from class com.mockturtlesolutions.snifflib.stats.ProbabilityDensity

GET_CDF, GET_ICDF, GET_PDF

Constructor Summary

Constructors

Constructor and Description
GammaDistribution()
GammaDistribution(DblMatrix alpha, DblMatrix beta)
GammaDistribution(DblMatrix alpha, double beta)
GammaDistribution(double alpha, DblMatrix beta)
GammaDistribution(double alpha, double beta)
GammaDistribution(int alpha, int beta)

Method Summary

Methods

Modifier and Type	Method and Description
DblMatrix	cdf(DblMatrix xx) CDF of the Normal distribution.
DblMatrix	criticalValue(DblMatrix cdfvals) For an input value C returns x such that P(X<=x) = C.
DblMatrix	getVariable()
DblMatrix	hasSupport(DblMatrix X) Returns 1 if the density has the input value in its support set (domain) and 0 otherwise.
DblMatrix	mean() Returns the expected value of the distribution for the currently configured parameters.
DblMatrix	median() Returns the median the distribution for the currently configured parameters.
DblMatrix	mode() Returns the mode the distribution for the currently configured parameters.
DblMatrix	pdf(DblMatrix X) Returns the value of the density function at X.
DblMatrix	random(int N) Return N random draws from this distribution.
void	setAlpha(DblMatrix u)
void	setBeta(DblMatrix beta)
void	setVariable(DblMatrix ff)
DblMatrix	variance() Returns the expected value of the distribution for the currently configured parameters.

Methods inherited from class com.mockturtlesolutions.snifflib.stats.ProbabilityDensity

assumeProbability, getAssumedProbability, getName, getParam, getParams, getValueAt, getValueToGet, getValueToMinimize, getVariableValue, hasParameter, parameterSet, replaceParams, setName, setParam, setValueToGet, setVariableValue

Methods inherited from class java.lang.Object

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

Constructor Detail

GammaDistribution

public GammaDistribution()

GammaDistribution

public GammaDistribution(DblMatrix alpha,
                 DblMatrix beta)

GammaDistribution

public GammaDistribution(double alpha,
                 DblMatrix beta)

GammaDistribution

public GammaDistribution(DblMatrix alpha,
                 double beta)

GammaDistribution

public GammaDistribution(double alpha,
                 double beta)

GammaDistribution

public GammaDistribution(int alpha,
                 int beta)

Method Detail

random

public DblMatrix random(int N)

Return N random draws from this distribution.

Overrides:

random in class ProbabilityDensity

setAlpha

public void setAlpha(DblMatrix u)

setBeta

public void setBeta(DblMatrix beta)

setVariable

public void setVariable(DblMatrix ff)

getVariable

public DblMatrix getVariable()

criticalValue

public DblMatrix criticalValue(DblMatrix cdfvals)

For an input value C returns x such that P(X<=x) = C. This is the inverse CDF of the distribution.

Specified by:

criticalValue in interface InvCDF

Specified by:

criticalValue in class ProbabilityDensity

pdf

public DblMatrix pdf(DblMatrix X)

Returns the value of the density function at X.

Specified by:

pdf in class ProbabilityDensity

hasSupport

public DblMatrix hasSupport(DblMatrix X)

Description copied from class: ProbabilityDensity

Returns 1 if the density has the input value in its support set (domain) and 0 otherwise.

Specified by:

hasSupport in class ProbabilityDensity

mean

public DblMatrix mean()

Returns the expected value of the distribution for the currently configured parameters.

median

public DblMatrix median()

Returns the median the distribution for the currently configured parameters. This implementation currently uses an approximate median calculation.

mode

public DblMatrix mode()

Returns the mode the distribution for the currently configured parameters.

variance

public DblMatrix variance()

Returns the expected value of the distribution for the currently configured parameters.

cdf

public DblMatrix cdf(DblMatrix xx)

CDF of the Normal distribution.

Specified by:

cdf in interface CDF

Specified by:

cdf in class ProbabilityDensity