org.spaceroots.mantissa.random

Class CorrelatedRandomVectorGenerator

java.lang.Object

org.spaceroots.mantissa.random.CorrelatedRandomVectorGenerator

All Implemented Interfaces:

java.io.Serializable, RandomVectorGenerator

public class CorrelatedRandomVectorGenerator
extends java.lang.Object
implements java.io.Serializable, RandomVectorGenerator

This class allows to generate random vectors with correlated components.

Random vectors with correlated components are built by combining the uncorrelated components of another random vector in such a way the resulting correlations are the ones specified by a positive definite covariance matrix.

Sometimes, the covariance matrix for a given simulation is not strictly positive definite. This means that the correlations are not all independant from each other. In this case, however, the non strictly positive elements found during the Cholesky decomposition of the covariance matrix should not be negative either, they should be null. This implies that rather than computing C = L.Lt where C is the covariance matrix and L is a lower-triangular matrix, we compute C = B.Bt where B is a rectangular matrix having more rows than columns. The number of columns of B is the rank of the covariance matrix, and it is the dimension of the uncorrelated random vector that is needed to compute the component of the correlated vector. This class does handle this situation automatically.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
CorrelatedRandomVectorGenerator(double[] mean, SymetricalMatrix covariance, NormalizedRandomGenerator generator) Simple constructor.
CorrelatedRandomVectorGenerator(SymetricalMatrix covariance, NormalizedRandomGenerator generator) Simple constructor.

Method Summary

Modifier and Type	Method and Description
NormalizedRandomGenerator	getGenerator() Get the underlying normalized components generator.
int	getRank() Get the rank of the covariance matrix.
Matrix	getRootMatrix() Get the root of the covariance matrix.
double[]	nextVector() Generate a correlated random vector.

Methods inherited from class java.lang.Object

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

Constructor Detail

CorrelatedRandomVectorGenerator

public CorrelatedRandomVectorGenerator(double[] mean,
                                       SymetricalMatrix covariance,
                                       NormalizedRandomGenerator generator)
                                throws NotPositiveDefiniteMatrixException

Simple constructor.

Build a correlated random vector generator from its mean vector and covariance matrix.

Parameters:

mean - expected mean values for all components

covariance - covariance matrix

generator - underlying generator for uncorrelated normalized components

Throws:

java.lang.IllegalArgumentException - if there is a dimension mismatch between the mean vector and the covariance matrix

NotPositiveDefiniteMatrixException - if the covariance matrix is not strictly positive definite

CorrelatedRandomVectorGenerator

public CorrelatedRandomVectorGenerator(SymetricalMatrix covariance,
                                       NormalizedRandomGenerator generator)
                                throws NotPositiveDefiniteMatrixException

Simple constructor.

Build a null mean random correlated vector generator from its covariance matrix.

Parameters:

covariance - covariance matrix

generator - underlying generator for uncorrelated normalized components

Throws:

NotPositiveDefiniteMatrixException - if the covariance matrix is not strictly positive definite

Method Detail

getRootMatrix

public Matrix getRootMatrix()

Get the root of the covariance matrix. The root is the matrix B such that B.Bt is equal to the covariance matrix

Returns:

root of the square matrix

getGenerator

public NormalizedRandomGenerator getGenerator()

Get the underlying normalized components generator.

Returns:

underlying uncorrelated components generator

getRank

public int getRank()

Get the rank of the covariance matrix. The rank is the number of independant rows in the covariance matrix, it is also the number of columns of the rectangular matrix of the factorization.

Returns:

rank of the square matrix.

nextVector

public double[] nextVector()

Generate a correlated random vector.

Specified by:

nextVector in interface RandomVectorGenerator

Returns:

a random vector as an array of double. The returned array is created at each call, the caller can do what it wants with it.