F07PHF (DSPRFS) (PDF version)
F07 Chapter Contents
F07 Chapter Introduction
NAG Library Manual

NAG Library Routine Document

F07PHF (DSPRFS)

Note:  before using this routine, please read the Users' Note for your implementation to check the interpretation of bold italicised terms and other implementation-dependent details.

+ Contents

    1  Purpose
    7  Accuracy

1  Purpose

F07PHF (DSPRFS) returns error bounds for the solution of a real symmetric indefinite system of linear equations with multiple right-hand sides, AX=B, using packed storage. It improves the solution by iterative refinement, in order to reduce the backward error as much as possible.

2  Specification

SUBROUTINE F07PHF ( UPLO, N, NRHS, AP, AFP, IPIV, B, LDB, X, LDX, FERR, BERR, WORK, IWORK, INFO)
INTEGER  N, NRHS, IPIV(*), LDB, LDX, IWORK(N), INFO
REAL (KIND=nag_wp)  AP(*), AFP(*), B(LDB,*), X(LDX,*), FERR(NRHS), BERR(NRHS), WORK(3*N)
CHARACTER(1)  UPLO
The routine may be called by its LAPACK name dsprfs.

3  Description

F07PHF (DSPRFS) returns the backward errors and estimated bounds on the forward errors for the solution of a real symmetric indefinite system of linear equations with multiple right-hand sides AX=B, using packed storage. The routine handles each right-hand side vector (stored as a column of the matrix B) independently, so we describe the function of F07PHF (DSPRFS) in terms of a single right-hand side b and solution x.
Given a computed solution x, the routine computes the component-wise backward error β. This is the size of the smallest relative perturbation in each element of A and b such that x is the exact solution of a perturbed system
A+δAx=b+δb δaijβaij   and   δbiβbi .
Then the routine estimates a bound for the component-wise forward error in the computed solution, defined by:
maxixi-x^i/maxixi
where x^ is the true solution.
For details of the method, see the F07 Chapter Introduction.

4  References

Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore

5  Parameters

1:     UPLO – CHARACTER(1)Input
On entry: specifies whether the upper or lower triangular part of A is stored and how A is to be factorized.
UPLO='U'
The upper triangular part of A is stored and A is factorized as PUDUTPT, where U is upper triangular.
UPLO='L'
The lower triangular part of A is stored and A is factorized as PLDLTPT, where L is lower triangular.
Constraint: UPLO='U' or 'L'.
2:     N – INTEGERInput
On entry: n, the order of the matrix A.
Constraint: N0.
3:     NRHS – INTEGERInput
On entry: r, the number of right-hand sides.
Constraint: NRHS0.
4:     AP(*) – REAL (KIND=nag_wp) arrayInput
Note: the dimension of the array AP must be at least max1,N×N+1/2.
On entry: the n by n original symmetric matrix A as supplied to F07PDF (DSPTRF).
5:     AFP(*) – REAL (KIND=nag_wp) arrayInput
Note: the dimension of the array AFP must be at least max1,N×N+1/2.
On entry: the factorization of A stored in packed form, as returned by F07PDF (DSPTRF).
6:     IPIV(*) – INTEGER arrayInput
Note: the dimension of the array IPIV must be at least max1,N.
On entry: details of the interchanges and the block structure of D, as returned by F07PDF (DSPTRF).
7:     B(LDB,*) – REAL (KIND=nag_wp) arrayInput
Note: the second dimension of the array B must be at least max1,NRHS.
On entry: the n by r right-hand side matrix B.
8:     LDB – INTEGERInput
On entry: the first dimension of the array B as declared in the (sub)program from which F07PHF (DSPRFS) is called.
Constraint: LDBmax1,N.
9:     X(LDX,*) – REAL (KIND=nag_wp) arrayInput/Output
Note: the second dimension of the array X must be at least max1,NRHS.
On entry: the n by r solution matrix X, as returned by F07PEF (DSPTRS).
On exit: the improved solution matrix X.
10:   LDX – INTEGERInput
On entry: the first dimension of the array X as declared in the (sub)program from which F07PHF (DSPRFS) is called.
Constraint: LDXmax1,N.
11:   FERR(NRHS) – REAL (KIND=nag_wp) arrayOutput
On exit: FERRj contains an estimated error bound for the jth solution vector, that is, the jth column of X, for j=1,2,,r.
12:   BERR(NRHS) – REAL (KIND=nag_wp) arrayOutput
On exit: BERRj contains the component-wise backward error bound β for the jth solution vector, that is, the jth column of X, for j=1,2,,r.
13:   WORK(3×N) – REAL (KIND=nag_wp) arrayWorkspace
14:   IWORK(N) – INTEGER arrayWorkspace
15:   INFO – INTEGEROutput
On exit: INFO=0 unless the routine detects an error (see Section 6).

6  Error Indicators and Warnings

Errors or warnings detected by the routine:
INFO<0
If INFO=-i, the ith parameter had an illegal value. An explanatory message is output, and execution of the program is terminated.

7  Accuracy

The bounds returned in FERR are not rigorous, because they are estimated, not computed exactly; but in practice they almost always overestimate the actual error.

8  Further Comments

For each right-hand side, computation of the backward error involves a minimum of 4n2 floating point operations. Each step of iterative refinement involves an additional 6n2 operations. At most five steps of iterative refinement are performed, but usually only 1 or 2 steps are required.
Estimating the forward error involves solving a number of systems of linear equations of the form Ax=b; the number is usually 4 or 5 and never more than 11. Each solution involves approximately 2n2 operations.
The complex analogues of this routine are F07PVF (ZHPRFS) for Hermitian matrices and F07QVF (ZSPRFS) for symmetric matrices.

9  Example

This example solves the system of equations AX=B using iterative refinement and to compute the forward and backward error bounds, where
A= 2.07 3.87 4.20 -1.15 3.87 -0.21 1.87 0.63 4.20 1.87 1.15 2.06 -1.15 0.63 2.06 -1.81   and   B= -9.50 27.85 -8.38 9.90 -6.07 19.25 -0.96 3.93 .
Here A is symmetric indefinite, stored in packed form, and must first be factorized by F07PDF (DSPTRF).

9.1  Program Text

Program Text (f07phfe.f90)

9.2  Program Data

Program Data (f07phfe.d)

9.3  Program Results

Program Results (f07phfe.r)


F07PHF (DSPRFS) (PDF version)
F07 Chapter Contents
F07 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2012