# SuanShu, a Java numerical and statistical library

com.numericalmethod.suanshu.algebra.linear.matrix.doubles.factorization.qr

## Class QR

• java.lang.Object
• com.numericalmethod.suanshu.algebra.linear.matrix.doubles.factorization.qr.QR
• All Implemented Interfaces:
QRDecomposition

public class QR
extends Object
implements QRDecomposition
QR decomposition of a matrix decomposes an m x n matrix A so that A = Q * R.
• Q is an m x n orthogonal matrix;
• R is a n x n upper triangular matrix.
Alternatively, we can have A = sqQ * tallR, where
• sqQ is a square m x m orthogonal matrix;
• tallR is a m x n matrix.
Wikipedia: QR decomposition
• ### Constructor Summary

Constructors
Constructor and Description
QR(Matrix A)
Run the QR decomposition on a matrix.
QR(Matrix A, double epsilon)
Run the QR decomposition on a matrix.
• ### Method Summary

All Methods
Modifier and Type Method and Description
PermutationMatrix P()
Get P, the pivoting matrix in the QR decomposition.
Matrix Q()
Get the orthogonal Q matrix in the QR decomposition, A = QR.
UpperTriangularMatrix R()
Get the upper triangular matrix R in the QR decomposition, A = QR.
int rank()
Get the numerical rank of A as computed by the QR decomposition.
Matrix squareQ()
Get the square Q matrix.
Matrix tallR()
Get the tall R matrix.
• ### Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
• ### Constructor Detail

• #### QR

public QR(Matrix A,
double epsilon)
Run the QR decomposition on a matrix.
Parameters:
A - a matrix
epsilon - a precision parameter: when a number |x| ≤ ε, it is considered 0
• #### QR

public QR(Matrix A)
Run the QR decomposition on a matrix.
Parameters:
A - a matrix
• ### Method Detail

• #### P

public PermutationMatrix P()
Description copied from interface: QRDecomposition
Get P, the pivoting matrix in the QR decomposition.
Specified by:
P in interface QRDecomposition
Returns:
P
• #### Q

public Matrix Q()
Description copied from interface: QRDecomposition
Get the orthogonal Q matrix in the QR decomposition, A = QR. The dimension of Q is m x n, the same as A, the matrix to be orthogonalized.
Specified by:
Q in interface QRDecomposition
Returns:
Q
• #### R

public UpperTriangularMatrix R()
Description copied from interface: QRDecomposition
Get the upper triangular matrix R in the QR decomposition, A = QR. The dimension of R is n x n, a square matrix.
Specified by:
R in interface QRDecomposition
Returns:
R
• #### rank

public int rank()
Description copied from interface: QRDecomposition
Get the numerical rank of A as computed by the QR decomposition. Numerical determination of rank requires a criterion to decide when a value should be treated as zero, hence a precision parameter. This is a practical choice which depends on both the matrix and the application. For instance, for a matrix with a big first eigenvector, we should accordingly decrease the precision to compute the rank.
Specified by:
rank in interface QRDecomposition
Returns:
the rank of A
• #### squareQ

public Matrix squareQ()
Description copied from interface: QRDecomposition
Get the square Q matrix. This is an arbitrary orthogonal completion of the Q matrix in the QR decomposition. The dimension is m x m (square). We have A = sqQ * tallR.
Specified by:
squareQ in interface QRDecomposition
Returns:
the square Q matrix
• #### tallR

public Matrix tallR()
Description copied from interface: QRDecomposition
Get the tall R matrix. This is completed by binding zero rows beneath the square upper triangular matrix R in the QR decomposition. The dimension is m x n. It may not be square. We have A = sqQ * tallR.
Specified by:
tallR in interface QRDecomposition
Returns:
the tall R matrix