org.apache.commons.math3.linear Class RRQRDecomposition

```java.lang.Object
org.apache.commons.math3.linear.QRDecomposition
org.apache.commons.math3.linear.RRQRDecomposition
```

`public class RRQRDecompositionextends QRDecomposition`

Calculates the rank-revealing QR-decomposition of a matrix, with column pivoting.

The rank-revealing QR-decomposition of a matrix A consists of three matrices Q, R and P such that AP=QR. Q is orthogonal (QTQ = I), and R is upper triangular. If A is m×n, Q is m×m and R is m×n and P is n×n.

QR decomposition with column pivoting produces a rank-revealing QR decomposition and the `getRank(double)` method may be used to return the rank of the input matrix A.

This class compute the decomposition using Householder reflectors.

For efficiency purposes, the decomposition in packed form is transposed. This allows inner loop to iterate inside rows, which is much more cache-efficient in Java.

This class is based on the class with similar name from the JAMA library, with the following changes:

Since:
3.2
Version:
\$Id: RRQRDecomposition.html 860130 2013-04-27 21:11:39Z luc \$
MathWorld, Wikipedia

Constructor Summary
`RRQRDecomposition(RealMatrix matrix)`
Calculates the QR-decomposition of the given matrix.
```RRQRDecomposition(RealMatrix matrix, double threshold)```
Calculates the QR-decomposition of the given matrix.

Method Summary
`protected  void` `decompose(double[][] qrt)`
Decompose matrix.
` RealMatrix` `getP()`
Returns the pivot matrix, P, used in the QR Decomposition of matrix A such that AP = QR.
` int` `getRank(double dropThreshold)`
Return the effective numerical matrix rank.
` DecompositionSolver` `getSolver()`
Get a solver for finding the A × X = B solution in least square sense.
`protected  void` ```performHouseholderReflection(int minor, double[][] qrt)```
Perform Householder reflection for a minor A(minor, minor) of A.

Methods inherited from class org.apache.commons.math3.linear.QRDecomposition
`getH, getQ, getQT, getR`

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

RRQRDecomposition

`public RRQRDecomposition(RealMatrix matrix)`
Calculates the QR-decomposition of the given matrix. The singularity threshold defaults to zero.

Parameters:
`matrix` - The matrix to decompose.
`RRQRDecomposition(RealMatrix, double)`

RRQRDecomposition

```public RRQRDecomposition(RealMatrix matrix,
double threshold)```
Calculates the QR-decomposition of the given matrix.

Parameters:
`matrix` - The matrix to decompose.
`threshold` - Singularity threshold.
`RRQRDecomposition(RealMatrix)`
Method Detail

decompose

`protected void decompose(double[][] qrt)`
Decompose matrix.

Overrides:
`decompose` in class `QRDecomposition`
Parameters:
`qrt` - transposed matrix

performHouseholderReflection

```protected void performHouseholderReflection(int minor,
double[][] qrt)```
Perform Householder reflection for a minor A(minor, minor) of A.

Overrides:
`performHouseholderReflection` in class `QRDecomposition`
Parameters:
`minor` - minor index
`qrt` - transposed matrix

getP

`public RealMatrix getP()`
Returns the pivot matrix, P, used in the QR Decomposition of matrix A such that AP = QR. If no pivoting is used in this decomposition then P is equal to the identity matrix.

Returns:
a permutation matrix.

getRank

`public int getRank(double dropThreshold)`
Return the effective numerical matrix rank.

The effective numerical rank is the number of non-negligible singular values.

This implementation looks at Frobenius norms of the sequence of bottom right submatrices. When a large fall in norm is seen, the rank is returned. The drop is computed as:

```   (thisNorm/lastNorm) * rNorm < dropThreshold
```

where thisNorm is the Frobenius norm of the current submatrix, lastNorm is the Frobenius norm of the previous submatrix, rNorm is is the Frobenius norm of the complete matrix

Parameters:
`dropThreshold` - threshold triggering rank computation
Returns:
effective numerical matrix rank

getSolver

`public DecompositionSolver getSolver()`
Get a solver for finding the A × X = B solution in least square sense.

Overrides:
`getSolver` in class `QRDecomposition`
Returns:
a solver