repicea.stats.distributions

Class UnknownDistribution

java.lang.Object

repicea.stats.distributions.UnknownDistribution

All Implemented Interfaces:

java.io.Serializable, CentralMomentsGettable, CentralMomentsSettable, Distribution

public class UnknownDistribution
extends java.lang.Object
implements Distribution, CentralMomentsSettable

The UnknownDistribution class is a basic distribution for which the first two moments are known (and can be set) but the underlying distribution remains unknown. NOTE the method getRandomObservation() always returns null for this class.

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from interface repicea.stats.Distribution

Distribution.Type

Constructor Summary

Constructors

Constructor and Description
UnknownDistribution()

Method Summary

Modifier and Type	Method and Description
Matrix	getMean() This method returns the first central moment, i.e.
Matrix	getRandomRealization() This method draws a random realization from the distribution.
Distribution.Type	getType() This method returns the type of the distribution.
Matrix	getVariance() This method returns the second central moment, i.e.
boolean	isMultivariate() This method returns true if the GaussianFunction instance is multivariate.
boolean	isParametric() This method returns true if the distribution is parametric or false otherwise.
void	setMean(Matrix mean) This method sets the mean vector of the random variable.
void	setVariance(Matrix variance) This method sets the variance-covariance matrix of the random variable.

Methods inherited from class java.lang.Object

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

Methods inherited from interface repicea.stats.Distribution

isUnivariate

Constructor Detail

UnknownDistribution

public UnknownDistribution()

Method Detail

isMultivariate

public boolean isMultivariate()

Description copied from interface: Distribution

This method returns true if the GaussianFunction instance is multivariate.

Specified by:

isMultivariate in interface Distribution

Returns:

a boolean

getMean

public Matrix getMean()

Description copied from interface: CentralMomentsGettable

This method returns the first central moment, i.e. the mean vector, of the random variable.

Specified by:

getMean in interface CentralMomentsGettable

Returns:

a Matrix instance

getVariance

public Matrix getVariance()

Description copied from interface: CentralMomentsGettable

This method returns the second central moment, i.e. the variance-covariance matrix, of the random variable.

Specified by:

getVariance in interface CentralMomentsGettable

Returns:

a Number instance

getType

public Distribution.Type getType()

Description copied from interface: Distribution

This method returns the type of the distribution.

Specified by:

getType in interface Distribution

Returns:

a Type enum

setMean

public void setMean(Matrix mean)

Description copied from interface: CentralMomentsSettable

This method sets the mean vector of the random variable.

Specified by:

setMean in interface CentralMomentsSettable

Parameters:

mean - a Matrix instance

setVariance

public void setVariance(Matrix variance)

Description copied from interface: CentralMomentsSettable

This method sets the variance-covariance matrix of the random variable.

Specified by:

setVariance in interface CentralMomentsSettable

Parameters:

variance - a Matrix instance

isParametric

public boolean isParametric()

Description copied from interface: Distribution

This method returns true if the distribution is parametric or false otherwise.

Specified by:

isParametric in interface Distribution

Returns:

a boolean

getRandomRealization

public Matrix getRandomRealization()

Description copied from interface: Distribution

This method draws a random realization from the distribution.

Specified by:

getRandomRealization in interface Distribution

Returns:

the observation in a Matrix instance