com.numericalmethod.suanshu.matrix.doubles.operation.positivedefinite

Class PositiveSemiDefiniteMatrixNonNegativeDiagonal

java.lang.Object

com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.DenseMatrix

com.numericalmethod.suanshu.matrix.doubles.operation.positivedefinite.PositiveDefiniteMatrixByPositiveDiagonal

com.numericalmethod.suanshu.matrix.doubles.operation.positivedefinite.PositiveSemiDefiniteMatrixNonNegativeDiagonal

All Implemented Interfaces:

Table, DeepCopyable, AbelianGroup<Matrix>, Monoid<Matrix>, Ring<Matrix>, Matrix, MatrixAccess, MatrixRing, MatrixTable, Densifiable, java.io.Serializable

public class PositiveSemiDefiniteMatrixNonNegativeDiagonal
extends PositiveDefiniteMatrixByPositiveDiagonal

This class "converts" a matrix into a symmetric, positive semi-definite matrix, if it is not already so, by forcing the negative diagonal entries in the eigen decomposition to 0.

See Also:

"Jin Wang, Chunlei Liu. "Generating Multivariate Mixture of Normal Distributions using a Modified Cholesky Decomposition," Simulation Conference, 2006. WSC 06. Proceedings of the Winter. p. 342 - 347. 3-6 Dec. 2006.", Serialized Form

Constructor Summary

Constructors

Constructor and Description
PositiveSemiDefiniteMatrixNonNegativeDiagonal(Matrix A, double epsilon) Construct a positive semi-definite matrix by forcing the negative diagonal entries in the eigen decomposition to 0.

Method Summary

Methods inherited from class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.DenseMatrix

add, deepCopy, equals, get, getColumn, getColumn, getRow, getRow, hashCode, minus, multiply, multiply, nCols, nRows, ONE, opposite, scaled, set, setColumn, setRow, t, toDense, toString, ZERO

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

PositiveSemiDefiniteMatrixNonNegativeDiagonal

public PositiveSemiDefiniteMatrixNonNegativeDiagonal(Matrix A,
                                                     double epsilon)

Construct a positive semi-definite matrix by forcing the negative diagonal entries in the eigen decomposition to 0.

Parameters:

A - a matrix

epsilon - a precision parameter: when a number |x| ≤ ε, it is considered 0; used in the eigen decomposition (don't make it 0)