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java.lang.Object javax.robotics.vecmath.jama.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 | |
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QRDecomposition(double[][] A,
int NumRow,
int NumCol)
QR Decomposition, computed by Householder reflections. |
Method Summary | |
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double[][] |
getH()
Return the Householder vectors |
double[][] |
getQ()
Generate and return the (economy-sized) orthogonal factor |
double[][] |
getR()
Return the upper triangular factor |
boolean |
isFullRank()
Is the matrix full rank? |
double[][] |
solve(double[][] B,
int NumRow,
int NumCol)
Least squares solution of A*X = B |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public QRDecomposition(double[][] A, int NumRow, int NumCol)
A
- Rectangular matrixMethod Detail |
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public boolean isFullRank()
public double[][] getH()
public double[][] getR()
public double[][] getQ()
public double[][] solve(double[][] B, int NumRow, int NumCol)
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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