org.apache.spark.mllib.stat.distribution

Class MultivariateGaussian

Object

org.apache.spark.mllib.stat.distribution.MultivariateGaussian

All Implemented Interfaces:

java.io.Serializable

public class MultivariateGaussian
extends Object
implements scala.Serializable

This class provides basic functionality for a Multivariate Gaussian (Normal) Distribution. In the event that the covariance matrix is singular, the density will be computed in a reduced dimensional subspace under which the distribution is supported. (see Degenerate case in Multivariate normal distribution (Wikipedia))

param: mu The mean vector of the distribution param: sigma The covariance matrix of the distribution

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
MultivariateGaussian(Vector mu, Matrix sigma)

Method Summary

Modifier and Type	Method and Description
double	logpdf(Vector x) Returns the log-density of this multivariate Gaussian at given point, x
Vector	mu()
double	pdf(Vector x) Returns density of this multivariate Gaussian at given point, x
Matrix	sigma()

Methods inherited from class Object

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

Constructor Detail

MultivariateGaussian

public MultivariateGaussian(Vector mu,
                            Matrix sigma)

Method Detail

logpdf

public double logpdf(Vector x)

Returns the log-density of this multivariate Gaussian at given point, x

Parameters:

x - (undocumented)

Returns:

(undocumented)

mu

public Vector mu()

pdf

public double pdf(Vector x)

Returns density of this multivariate Gaussian at given point, x

Parameters:

x - (undocumented)

Returns:

(undocumented)

sigma

public Matrix sigma()