org.apache.commons.math3.distribution
Class AbstractMultivariateRealDistribution

java.lang.Object
  org.apache.commons.math3.distribution.AbstractMultivariateRealDistribution

All Implemented Interfaces:

MultivariateRealDistribution

Direct Known Subclasses:

MixtureMultivariateRealDistribution, MultivariateNormalDistribution

public abstract class AbstractMultivariateRealDistribution
extends Object
implements MultivariateRealDistribution

Base class for multivariate probability distributions.

Since:

3.1

Version:

$Id: AbstractMultivariateRealDistribution.java 1416643 2012-12-03 19:37:14Z tn $

random

protected final RandomGenerator random

RNG instance used to generate samples from the distribution.

AbstractMultivariateRealDistribution

protected AbstractMultivariateRealDistribution(RandomGenerator rng,
                                               int n)

Parameters:

rng - Random number generator.

n - Number of dimensions.

reseedRandomGenerator

public void reseedRandomGenerator(long seed)

Reseeds the random generator used to generate samples.

Specified by:

reseedRandomGenerator in interface MultivariateRealDistribution

Parameters:

seed - Seed with which to initialize the random number generator.

getDimension

public int getDimension()

Gets the number of random variables of the distribution. It is the size of the array returned by the sample method.

Specified by:

getDimension in interface MultivariateRealDistribution

Returns:

the number of variables.

sample

public abstract double[] sample()

Generates a random value vector sampled from this distribution.

Specified by:

sample in interface MultivariateRealDistribution

Returns:

a random value vector.

sample

public double[][] sample(int sampleSize)

Generates a list of a random value vectors from the distribution.

Specified by:

sample in interface MultivariateRealDistribution

Parameters:

sampleSize - the number of random vectors to generate.

Returns:

an array representing the random samples.

See Also:

MultivariateRealDistribution.sample()