public class QRDecomposition extends Object implements Serializable
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.
| Constructor and Description |
|---|
QRDecomposition(Matrix A)
QR Decomposition, computed by Householder reflections.
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| 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 B)
Least squares solution of A*X = B
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public QRDecomposition(Matrix A)
A - Rectangular matrixpublic boolean isFullRank()
public Matrix getH()
public Matrix getR()
public Matrix getQ()
public Matrix solve(Matrix B)
B - A Matrix with as many rows as A and any number of columns.IllegalArgumentException - Matrix row dimensions must agree.RuntimeException - Matrix is rank deficient.Jas4pp 1.5 © Java Analysis Studio for Particle Physics