NAG Library Routine Document
F07GHF (DPPRFS)
1 Purpose
F07GHF (DPPRFS) returns error bounds for the solution of a real symmetric positive definite system of linear equations with multiple right-hand sides, , using packed storage. It improves the solution by iterative refinement, in order to reduce the backward error as much as possible.
2 Specification
SUBROUTINE F07GHF ( |
UPLO, N, NRHS, AP, AFP, B, LDB, X, LDX, FERR, BERR, WORK, IWORK, INFO) |
INTEGER |
N, NRHS, 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 dpprfs.
3 Description
F07GHF (DPPRFS) returns the backward errors and estimated bounds on the forward errors for the solution of a real symmetric positive definite system of linear equations with multiple right-hand sides , using packed storage. The routine handles each right-hand side vector (stored as a column of the matrix ) independently, so we describe the function of F07GHF (DPPRFS) in terms of a single right-hand side and solution .
Given a computed solution
, the routine computes the
component-wise backward error . This is the size of the smallest relative perturbation in each element of
and
such that
is the exact solution of a perturbed system
Then the routine estimates a bound for the
component-wise forward error in the computed solution, defined by:
where
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
is stored and how
is to be factorized.
- The upper triangular part of is stored and is factorized as , where is upper triangular.
- The lower triangular part of is stored and is factorized as , where is lower triangular.
Constraint:
or .
- 2: N – INTEGERInput
On entry: , the order of the matrix .
Constraint:
.
- 3: NRHS – INTEGERInput
On entry: , the number of right-hand sides.
Constraint:
.
- 4: AP() – REAL (KIND=nag_wp) arrayInput
-
Note: the dimension of the array
AP
must be at least
.
On entry: the
by
original symmetric positive definite matrix
as supplied to
F07GDF (DPPTRF).
- 5: AFP() – REAL (KIND=nag_wp) arrayInput
-
Note: the dimension of the array
AFP
must be at least
.
On entry: the Cholesky factor of
stored in packed form, as returned by
F07GDF (DPPTRF).
- 6: B(LDB,) – REAL (KIND=nag_wp) arrayInput
-
Note: the second dimension of the array
B
must be at least
.
On entry: the by right-hand side matrix .
- 7: LDB – INTEGERInput
On entry: the first dimension of the array
B as declared in the (sub)program from which F07GHF (DPPRFS) is called.
Constraint:
.
- 8: X(LDX,) – REAL (KIND=nag_wp) arrayInput/Output
-
Note: the second dimension of the array
X
must be at least
.
On entry: the
by
solution matrix
, as returned by
F07GEF (DPPTRS).
On exit: the improved solution matrix .
- 9: LDX – INTEGERInput
On entry: the first dimension of the array
X as declared in the (sub)program from which F07GHF (DPPRFS) is called.
Constraint:
.
- 10: FERR(NRHS) – REAL (KIND=nag_wp) arrayOutput
On exit: contains an estimated error bound for the th solution vector, that is, the th column of , for .
- 11: BERR(NRHS) – REAL (KIND=nag_wp) arrayOutput
On exit: contains the component-wise backward error bound for the th solution vector, that is, the th column of , for .
- 12: WORK() – REAL (KIND=nag_wp) arrayWorkspace
- 13: IWORK(N) – INTEGER arrayWorkspace
- 14: INFO – INTEGEROutput
On exit:
unless the routine detects an error (see
Section 6).
6 Error Indicators and Warnings
Errors or warnings detected by the routine:
If , the th 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.
For each right-hand side, computation of the backward error involves a minimum of floating point operations. Each step of iterative refinement involves an additional operations. At most five steps of iterative refinement are performed, but usually only or steps are required.
Estimating the forward error involves solving a number of systems of linear equations of the form ; the number is usually or and never more than . Each solution involves approximately operations.
The complex analogue of this routine is
F07GVF (ZPPRFS).
9 Example
This example solves the system of equations
using iterative refinement and to compute the forward and backward error bounds, where
Here
is symmetric positive definite, stored in packed form, and must first be factorized by
F07GDF (DPPTRF).
9.1 Program Text
Program Text (f07ghfe.f90)
9.2 Program Data
Program Data (f07ghfe.d)
9.3 Program Results
Program Results (f07ghfe.r)