org.apache.commons.math3.linear

## Class RectangularCholeskyDecomposition

- java.lang.Object
- - org.apache.commons.math3.linear.RectangularCholeskyDecomposition

    public class RectangularCholeskyDecomposition
    extends java.lang.Object

Calculates the rectangular Cholesky decomposition of a matrix.

The rectangular Cholesky decomposition of a real symmetric positive semidefinite matrix A consists of a rectangular matrix B with the same number of rows such that: A is almost equal to BBT, depending on a user-defined tolerance. In a sense, this is the square root of A.

The difference with respect to the regular `CholeskyDecomposition` is that rows/columns may be permuted (hence the rectangular shape instead of the traditional triangular shape) and there is a threshold to ignore small diagonal elements. This is used for example to generate `correlated random n-dimensions vectors` in a p-dimension subspace (p < n). In other words, it allows generating random vectors from a covariance matrix that is only positive semidefinite, and not positive definite.

Rectangular Cholesky decomposition is not suited for solving linear systems, so it does not provide any `decomposition solver`.

Since:
  2.0 (changed to concrete class in 3.0)
Version:
  $Id: RectangularCholeskyDecomposition.java 1422313 2012-12-15 18:53:41Z psteitz $
See Also:
  MathWorld, Wikipedia

### Field Summary

Fields
`private int` `rank` Rank of the symmetric positive semidefinite matrix.
`private RealMatrix` `root` Permutated Cholesky root of the symmetric positive semidefinite matrix.

### Constructor Summary

Constructors
Constructor and Description
`RectangularCholeskyDecomposition(RealMatrix matrix)` Decompose a symmetric positive semidefinite matrix.
`RectangularCholeskyDecomposition(RealMatrix matrix, double small)` Decompose a symmetric positive semidefinite matrix.

### Method Summary

Methods
`int` `getRank()` Get the rank of the symmetric positive semidefinite matrix.
`RealMatrix` `getRootMatrix()` Get the root of the covariance matrix.

### Methods inherited from class java.lang.Object

`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

### Field Detail

#### root

    private final RealMatrix root

Permutated Cholesky root of the symmetric positive semidefinite matrix.

#### rank

    private int rank

Rank of the symmetric positive semidefinite matrix.

### Constructor Detail

#### RectangularCholeskyDecomposition

    public RectangularCholeskyDecomposition(RealMatrix matrix)
                                     throws NonPositiveDefiniteMatrixException

Decompose a symmetric positive semidefinite matrix.

Note: this constructor follows the linpack method to detect dependent columns by proceeding with the Cholesky algorithm until a nonpositive diagonal element is encountered.

Parameters:
  `matrix` - Symmetric positive semidefinite matrix.
Throws:
  `NonPositiveDefiniteMatrixException` - if the matrix is not positive semidefinite.
Since:
  3.1
See Also:
  Analysis of the Cholesky Decomposition of a Semi-definite Matrix

#### RectangularCholeskyDecomposition

    public RectangularCholeskyDecomposition(RealMatrix matrix,
                                    double small)
                                     throws NonPositiveDefiniteMatrixException

Decompose a symmetric positive semidefinite matrix.

Parameters:
  `matrix` - Symmetric positive semidefinite matrix.
  `small` - Diagonal elements threshold under which columns are considered to be dependent on previous ones and are discarded.
Throws:
  `NonPositiveDefiniteMatrixException` - if the matrix is not positive semidefinite.

### Method Detail

#### getRootMatrix

    public RealMatrix getRootMatrix()

Get the root of the covariance matrix. The root is the rectangular matrix `B` such that the covariance matrix is equal to `B.BT`

Returns:
  root of the square matrix
See Also:
  `getRank()`

#### getRank

    public int getRank()

Get the rank of the symmetric positive semidefinite matrix. The r is the number of independent rows in the symmetric positive semidefinite matrix, it is also the number of columns of the rectangular matrix of the decomposition.

Returns:
  r of the square matrix.
See Also:
  `getRootMatrix()`