org.ddogleg.rand

Class MultivariateGaussianDraw

java.lang.Object

org.ddogleg.rand.MultivariateGaussianDraw

public class MultivariateGaussianDraw
extends java.lang.Object

Draw a number from a multivariate Gaussian distribution.

Constructor Summary

Constructors

Constructor and Description
MultivariateGaussianDraw(java.util.Random rand, org.ejml.data.DenseMatrix64F mean, org.ejml.data.DenseMatrix64F cov) Creates a random distribution with the specified mean and covariance.

Method Summary

Modifier and Type	Method and Description
void	assignMean(org.ejml.data.DenseMatrix64F mean) Uses the referenced variable as the internal mean.
double	computeLikelihoodP()
org.ejml.data.DenseMatrix64F	next(org.ejml.data.DenseMatrix64F x) Makes a draw on the distribution and stores the results in parameter 'x'

Methods inherited from class java.lang.Object

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

Constructor Detail

MultivariateGaussianDraw

public MultivariateGaussianDraw(java.util.Random rand,
                                org.ejml.data.DenseMatrix64F mean,
                                org.ejml.data.DenseMatrix64F cov)

Creates a random distribution with the specified mean and covariance. The references to the variables are not saved, their value are copied.

Parameters:

rand - Used to create the random numbers for the draw.

mean - If not null this will be the mean of the distribution, if null then nothing is assigned. this is useful if someone is being anal about performance and will soon call assignMean()

cov - The covariance of the distribution

Method Detail

assignMean

public void assignMean(org.ejml.data.DenseMatrix64F mean)

Uses the referenced variable as the internal mean. This does not perform a copy but actually points to the specified matrix as the mean.

next

public org.ejml.data.DenseMatrix64F next(org.ejml.data.DenseMatrix64F x)

Makes a draw on the distribution and stores the results in parameter 'x'

computeLikelihoodP

public double computeLikelihoodP()