F04BHF (PDF version)
F04 Chapter Contents
F04 Chapter Introduction
NAG Library Manual

NAG Library Routine Document

F04BHF

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

F04BHF computes the solution to a real system of linear equations AX=B, where A is an n by n symmetric matrix and X and B are n by r matrices. An estimate of the condition number of A and an error bound for the computed solution are also returned.

2  Specification

SUBROUTINE F04BHF ( UPLO, N, NRHS, A, LDA, IPIV, B, LDB, RCOND, ERRBND, IFAIL)
INTEGER  N, NRHS, LDA, IPIV(N), LDB, IFAIL
REAL (KIND=nag_wp)  A(LDA,*), B(LDB,*), RCOND, ERRBND
CHARACTER(1)  UPLO

3  Description

The diagonal pivoting method is used to factor A as A=UDUT, if UPLO='U', or A=LDLT, if UPLO='L', where U (or L) is a product of permutation and unit upper (lower) triangular matrices, and D is symmetric and block diagonal with 1 by 1 and 2 by 2 diagonal blocks. The factored form of A is then used to solve the system of equations AX=B.

4  References

Anderson E, Bai Z, Bischof C, Blackford S, Demmel J, Dongarra J J, Du Croz J J, Greenbaum A, Hammarling S, McKenney A and Sorensen D (1999) LAPACK Users' Guide (3rd Edition) SIAM, Philadelphia http://www.netlib.org/lapack/lug
Higham N J (2002) Accuracy and Stability of Numerical Algorithms (2nd Edition) SIAM, Philadelphia

5  Parameters

1:     UPLO – CHARACTER(1)Input
On entry: if UPLO='U', the upper triangle of the matrix A is stored.
If UPLO='L', the lower triangle of the matrix A is stored.
Constraint: UPLO='U' or 'L'.
2:     N – INTEGERInput
On entry: the number of linear equations n, i.e., the order of the matrix A.
Constraint: N0.
3:     NRHS – INTEGERInput
On entry: the number of right-hand sides r, i.e., the number of columns of the matrix B.
Constraint: NRHS0.
4:     A(LDA,*) – REAL (KIND=nag_wp) arrayInput/Output
Note: the second dimension of the array A must be at least max1,N.
On entry: the n by n symmetric matrix A.
If UPLO='U', the leading N by N upper triangular part of the array A contains the upper triangular part of the matrix A, and the strictly lower triangular part of A is not referenced.
If UPLO='L', the leading N by N lower triangular part of the array A contains the lower triangular part of the matrix A, and the strictly upper triangular part of A is not referenced.
On exit: if IFAIL0, the block diagonal matrix D and the multipliers used to obtain the factor U or L from the factorization A=UDUT or A=LDLT as computed by F07MDF (DSYTRF).
5:     LDA – INTEGERInput
On entry: the first dimension of the array A as declared in the (sub)program from which F04BHF is called.
Constraint: LDAmax1,N.
6:     IPIV(N) – INTEGER arrayOutput
On exit: if IFAIL0, details of the interchanges and the block structure of D, as determined by F07MDF (DSYTRF).
IPIVk>0
Rows and columns k and IPIVk were interchanged, and dkk is a 1 by 1 diagonal block.
UPLO='U' and IPIVk=IPIVk-1<0
Rows and columns k-1 and -IPIVk were interchanged and dk-1:k,k-1:k is a 2 by 2 diagonal block.
UPLO='L' and IPIVk=IPIVk+1<0
Rows and columns k+1 and -IPIVk were interchanged and dk:k+1,k:k+1 is a 2 by 2 diagonal block.
7:     B(LDB,*) – REAL (KIND=nag_wp) arrayInput/Output
Note: the second dimension of the array B must be at least max1,NRHS.
On entry: the n by r matrix of right-hand sides B.
On exit: if IFAIL=0 or N+1, the n by r solution matrix X.
8:     LDB – INTEGERInput
On entry: the first dimension of the array B as declared in the (sub)program from which F04BHF is called.
Constraint: LDBmax1,N.
9:     RCOND – REAL (KIND=nag_wp)Output
On exit: if no constraints are violated, an estimate of the reciprocal of the condition number of the matrix A, computed as RCOND=1/A1A-11.
10:   ERRBND – REAL (KIND=nag_wp)Output
On exit: if IFAIL=0 or N+1, an estimate of the forward error bound for a computed solution x^, such that x^-x1/x1ERRBND, where x^ is a column of the computed solution returned in the array B and x is the corresponding column of the exact solution X. If RCOND is less than machine precision, then ERRBND is returned as unity.
11:   IFAIL – INTEGERInput/Output
On entry: IFAIL must be set to 0, -1​ or ​1. If you are unfamiliar with this parameter you should refer to Section 3.3 in the Essential Introduction for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value -1​ or ​1 is recommended. If the output of error messages is undesirable, then the value 1 is recommended. Otherwise, if you are not familiar with this parameter, the recommended value is 0. When the value -1​ or ​1 is used it is essential to test the value of IFAIL on exit.
On exit: IFAIL=0 unless the routine detects an error or a warning has been flagged (see Section 6).

6  Error Indicators and Warnings

If on entry IFAIL=0 or -1, explanatory error messages are output on the current error message unit (as defined by X04AAF).
Errors or warnings detected by the routine:
IFAIL<0 and IFAIL-999
If IFAIL=-i, the ith argument had an illegal value.
IFAIL=-999
Allocation of memory failed. The integer allocatable memory required is N, and the real allocatable memory required is max2×N,LWORK, where LWORK is the optimum workspace required by F07MAF (DSYSV). If this failure occurs it may be possible to solve the equations by calling the packed storage version of F04BHF, F04BJF, or by calling F07MAF (DSYSV) directly with less than the optimum workspace (see Chapter F07).
IFAIL>0 and IFAILN
If IFAIL=i, dii is exactly zero. The factorization has been completed, but the block diagonal matrix D is exactly singular, so the solution could not be computed.
IFAIL=N+1
RCOND is less than machine precision, so that the matrix A is numerically singular. A solution to the equations AX=B has nevertheless been computed.

7  Accuracy

The computed solution for a single right-hand side, x^, satisfies an equation of the form
A+E x^ = b ,
where
E1 = Oε A1
and ε is the machine precision. An approximate error bound for the computed solution is given by
x^-x1 x1 κA E1 A1 ,
where κA = A-11 A1 , the condition number of A with respect to the solution of the linear equations. F04BHF uses the approximation E1=εA1 to estimate ERRBND. See Section 4.4 of Anderson et al. (1999) for further details.

8  Further Comments

The total number of floating point operations required to solve the equations AX=B is proportional to 13n3+2n2r. The condition number estimation typically requires between four and five solves and never more than eleven solves, following the factorization.
In practice the condition number estimator is very reliable, but it can underestimate the true condition number; see Section 15.3 of Higham (2002) for further details.
The complex analogues of F04BHF are F04CHF for complex Hermitian matrices, and F04DHF for complex symmetric matrices.

9  Example

This example solves the equations
AX=B,
where A is the symmetric indefinite matrix
A= -1.81 2.06 0.63 -1.15 2.06 1.15 1.87 4.20 0.63 1.87 -0.21 3.87 -1.15 4.20 3.87 2.07   and   B= 0.96 3.93 6.07 19.25 8.38 9.90 9.50 27.85 .
An estimate of the condition number of A and an approximate error bound for the computed solutions are also printed.

9.1  Program Text

Program Text (f04bhfe.f90)

9.2  Program Data

Program Data (f04bhfe.d)

9.3  Program Results

Program Results (f04bhfe.r)


F04BHF (PDF version)
F04 Chapter Contents
F04 Chapter Introduction
NAG Library Manual

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