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java.lang.Objectorg.openmali.decomposition.QRDecomposition
public class QRDecomposition
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.
| Constructor Summary | |
|---|---|
QRDecomposition(MatrixMxNf A)
QR Decomposition, computed by Householder reflections. |
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| Method Summary | |
|---|---|
MatrixMxNf |
getH()
Returns the Householder vectors. |
MatrixMxNf |
getQ()
|
MatrixMxNf |
getR()
|
boolean |
isFullRank()
Is the matrix full rank? |
MatrixMxNf |
solve(MatrixMxNf B,
MatrixMxNf result)
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 |
|---|
public QRDecomposition(MatrixMxNf A)
A - Rectangular matrix| Method Detail |
|---|
public final boolean isFullRank()
public MatrixMxNf getH()
public MatrixMxNf getR()
public MatrixMxNf getQ()
public final MatrixMxNf solve(MatrixMxNf B,
MatrixMxNf result)
B - A Matrix with as many rows as A and any number of columns.
java.lang.IllegalArgumentException - Matrix row dimensions must agree.
java.lang.RuntimeException - Matrix is rank deficient.
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