com.mockturtlesolutions.snifflib.stats

Class TDistribution

java.lang.Object

com.mockturtlesolutions.snifflib.stats.ProbabilityDensity

com.mockturtlesolutions.snifflib.stats.TDistribution

All Implemented Interfaces:

NamedParameters, OptimizableScalar, CDF, InvCDF

public class TDistribution
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
TDistribution()
TDistribution(DblMatrix nu)
TDistribution(double nu)
TDistribution(int nu)

Method Summary

Methods

Modifier and Type	Method and Description
DblMatrix	cdf(DblMatrix xx) CDF of the T distribution.
DblMatrix	criticalValue(DblMatrix cdfval) 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 of the distribution for the currently configured parameters.
DblMatrix	mode() Returns the mode of 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	setDF(DblMatrix m)
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

TDistribution

public TDistribution()

TDistribution

public TDistribution(int nu)

TDistribution

public TDistribution(double nu)

TDistribution

public TDistribution(DblMatrix nu)

Method Detail

setDF

public void setDF(DblMatrix m)

random

public DblMatrix random(int N)

Return N random draws from this distribution.

Overrides:

random in class ProbabilityDensity

setVariable

public void setVariable(DblMatrix ff)

getVariable

public DblMatrix getVariable()

criticalValue

public DblMatrix criticalValue(DblMatrix cdfval)

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

median

public DblMatrix median()

Returns the median of the distribution for the currently configured parameters.

mode

public DblMatrix mode()

Returns the mode of the distribution for the currently configured parameters.

mean

public DblMatrix mean()

Returns the expected value of 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 T distribution.

Specified by:

cdf in interface CDF

Specified by:

cdf in class ProbabilityDensity