be.ac.ulg.montefiore.run.distributions
Class MultiGaussianDistribution

java.lang.Object
  be.ac.ulg.montefiore.run.distributions.MultiGaussianDistribution

All Implemented Interfaces:

MultiRandomDistribution, java.io.Serializable

public class MultiGaussianDistribution
extends java.lang.Object
implements MultiRandomDistribution

This class implements a multi-variate Gaussian distribution.

See Also:

Serialized Form

Constructor Summary

MultiGaussianDistribution(double[] mean, double[][] covariance)
Creates a new pseudo-random, multivariate gaussian distribution.

MultiGaussianDistribution(int dimension)
Creates a new pseudo-random, multivariate gaussian distribution with zero mean and identity covariance.

Method Summary

double[][]	covariance() Returns (a copy of) this distribution's covariance matrix.
double	covarianceDet() Returns the covariance matrix determinant.
int	dimension() Returns the dimension of the vectors handled by this random distribution.
double[]	generate() Generates a pseudo-random vector according to this distribution.
double[]	mean() Returns (a copy of) this distribution's mean vector.
double	probability(double[] v) Returns the probability (density) of a given vector.

Methods inherited from class java.lang.Object

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

Constructor Detail

MultiGaussianDistribution

public MultiGaussianDistribution(double[] mean,
                                 double[][] covariance)

Creates a new pseudo-random, multivariate gaussian distribution.

Parameters:

mean - The mean vector of the generated numbers. This array is copied.

covariance - The covariance of the generated numbers. This array is copied. covariance[r][c] is the element at row r and column c.

MultiGaussianDistribution

public MultiGaussianDistribution(int dimension)

Creates a new pseudo-random, multivariate gaussian distribution with zero mean and identity covariance.

Parameters:

dimension - This distribution dimension.

Method Detail

dimension

public int dimension()

Description copied from interface: MultiRandomDistribution

Returns the dimension of the vectors handled by this random distribution.

Specified by:

dimension in interface MultiRandomDistribution

Returns:

The generated vectors' dimension.

mean

public double[] mean()

Returns (a copy of) this distribution's mean vector.

Returns:

This distribution's mean vector.

covariance

public double[][] covariance()

Returns (a copy of) this distribution's covariance matrix.

Returns:

This distribution's covariance matrix.

covarianceDet

public double covarianceDet()

Returns the covariance matrix determinant.

Returns:

The covariance matrix determinant.

generate

public double[] generate()

Generates a pseudo-random vector according to this distribution. The vectors are generated using the Cholesky decomposition of the covariance matrix.

Specified by:

generate in interface MultiRandomDistribution

Returns:

A pseudo-random vector.

probability

public double probability(double[] v)

Description copied from interface: MultiRandomDistribution

Returns the probability (density) of a given vector.

Specified by:

probability in interface MultiRandomDistribution

Parameters:

v - A vector.

Returns:

The probability of the vector v.