com.helger.matrix

Class QRDecomposition

java.lang.Object

com.helger.matrix.QRDecomposition

All Implemented Interfaces:

Serializable

public class QRDecomposition
extends Object
implements Serializable

QR Decomposition.

For an m-by-n matrix A with m ≥ n, the QR decomposition is an m-by-n orthogonal matrix Q and an n-by-n upper triangular matrix R so that A = Q*R.

The QR decompostion always exists, even if the matrix does not have full rank, so the constructor will never fail. The primary use of the QR decomposition is in the least squares solution of nonsquare systems of simultaneous linear equations. This will fail if isFullRank() returns false.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
QRDecomposition(Matrix aMatrix) QR Decomposition, computed by Householder reflections.

Method Summary

Modifier and Type	Method and Description
Matrix	getH() Return the Householder vectors
Matrix	getQ() Generate and return the (economy-sized) orthogonal factor
Matrix	getR() Return the upper triangular factor
boolean	isFullRank() Is the matrix full rank?
Matrix	solve(Matrix aMatrix) Least squares solution of A*X = B

Methods inherited from class java.lang.Object

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

Constructor Detail

QRDecomposition

public QRDecomposition(@Nonnull
                       Matrix aMatrix)

QR Decomposition, computed by Householder reflections. Structure to access R and the Householder vectors and compute Q.

Parameters:

aMatrix - Rectangular matrix

Method Detail

isFullRank

public boolean isFullRank()

Is the matrix full rank?

Returns:

true if R, and hence A, has full rank.

getH

@Nonnull
 @ReturnsMutableCopy
public Matrix getH()

Return the Householder vectors

Returns:

Lower trapezoidal matrix whose columns define the reflections

getR

@Nonnull
 @ReturnsMutableCopy
public Matrix getR()

Return the upper triangular factor

Returns:

R

getQ

@Nonnull
 @ReturnsMutableCopy
public Matrix getQ()

Generate and return the (economy-sized) orthogonal factor

Returns:

Q

solve

@Nonnull
 @ReturnsMutableCopy
public Matrix solve(@Nonnull
                                                    Matrix aMatrix)

Least squares solution of A*X = B

Parameters:

aMatrix - A Matrix with as many rows as A and any number of columns.

Returns:

X that minimizes the two norm of Q*R*X-B.

Throws:

IllegalArgumentException - Matrix row dimensions must agree.

RuntimeException - Matrix is rank deficient.