Class CorrelatedVectorFactory
 java.lang.Object

 org.apache.commons.math4.legacy.random.CorrelatedVectorFactory

public class CorrelatedVectorFactory extends Object
Generates vectors with with correlated components.Random vectors with correlated components are built by combining the uncorrelated components of another random vector in such a way that the resulting correlations are the ones specified by a positive definite covariance matrix.
The main use of correlated random vector generation is for MonteCarlo simulation of physical problems with several variables (for example to generate error vectors to be added to a nominal vector). A particularly common case is when the generated vector should be drawn from a Multivariate Normal Distribution, usually using Cholesky decomposition. Other distributions are possible as long as the underlying sampler provides normalized values (unit standard deviation).
Sometimes, the covariance matrix for a given simulation is not strictly positive definite. This means that the correlations are not all independent 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. Another nonconventional extension handling this case is used here. Rather than computing
C = U^{T} U
whereC
is the covariance matrix andU
is an uppertriangular matrix, we computeC = B B^{T}
whereB
is a rectangular matrix having more rows than columns. The number of columns ofB
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 handles this situation automatically.


Constructor Summary
Constructors Constructor Description CorrelatedVectorFactory(double[] mean, RealMatrix covariance, double small)
Correlated vector factory.CorrelatedVectorFactory(RealMatrix covariance, double small)
Null mean correlated vector factory.

Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description Supplier<double[]>
gaussian(org.apache.commons.rng.UniformRandomProvider rng)
Supplier<double[]>
uniform(org.apache.commons.rng.UniformRandomProvider rng)



Constructor Detail

CorrelatedVectorFactory
public CorrelatedVectorFactory(double[] mean, RealMatrix covariance, double small)
Correlated vector factory. Parameters:
mean
 Expected mean values of the components.covariance
 Covariance matrix.small
 Diagonal elements threshold under which columns are considered to be dependent on previous ones and are discarded. Throws:
NonPositiveDefiniteMatrixException
 if the covariance matrix is not strictly positive definite.DimensionMismatchException
 if the mean and covariance arrays dimensions do not match.

CorrelatedVectorFactory
public CorrelatedVectorFactory(RealMatrix covariance, double small)
Null mean correlated vector factory. Parameters:
covariance
 Covariance matrix.small
 Diagonal elements threshold under which columns are considered to be dependent on previous ones and are discarded. Throws:
NonPositiveDefiniteMatrixException
 if the covariance matrix is not strictly positive definite.

