Integer, Intent (In)	::	n, lda, ipiv(*)
Integer, Intent (Out)	::	iwork(n), info
Real (Kind=nag_wp), Intent (In)	::	a(lda,*), anorm
Real (Kind=nag_wp), Intent (Out)	::	rcond, work(2*n)
Character (1), Intent (In)	::	uplo

C Header Interface

#include <nag.h>

void	f07mgf_ (const char uplo, const Integer n, const double a[], const Integer lda, const Integer ipiv[], const double anorm, double rcond, double work[], Integer iwork[], Integer info, const Charlen length_uplo)

The routine may be called by the names f07mgf, nagf_lapacklin_dsycon or its LAPACK name dsycon.

3 Description

f07mgf estimates the condition number (in the

1

-norm) of a real symmetric indefinite matrix

A

κ_{1} (A) = {‖ A ‖}_{1} {‖ A^{- 1} ‖}_{1} .

Since

A

is symmetric,

κ_{1} (A) = κ_{\infty} (A) = {‖ A ‖}_{\infty} {‖ A^{- 1} ‖}_{\infty}

Because

κ_{1} (A)

is infinite if

A

is singular, the routine actually returns an estimate of the reciprocal of

κ_{1} (A)

The routine should be preceded by a call to f06rcf to compute

{‖ A ‖}_{1}

and a call to f07mdf to compute the Bunch–Kaufman factorization of

A

. The routine then uses Higham's implementation of Hager's method (see Higham (1988)) to estimate

{‖ A^{- 1} ‖}_{1}

4 References

Higham N J (1988) FORTRAN codes for estimating the one-norm of a real or complex matrix, with applications to condition estimation ACM Trans. Math. Software 14 381–396

5 Arguments

1: $uplo$ – Character(1) Input

On entry: specifies how

A

has been factorized.

$uplo ='U'$: $A = P U D U^{T} P^{T}$ , where $U$ is upper triangular.
$uplo ='L'$: $A = P L D L^{T} P^{T}$ , where $L$ is lower triangular.

Constraint:

uplo ='U'

'L'

2: $n$ – Integer Input

On entry:

n

, the order of the matrix

A

Constraint:

n \geq 0

3: $a (lda, *)$ – Real (Kind=nag_wp) array Input

Note: the second dimension of the array a must be at least

\max (1, n)

On entry: details of the factorization of

A

, as returned by f07mdf.

4: $lda$ – Integer Input

On entry: the first dimension of the array a as declared in the (sub)program from which f07mgf is called.

Constraint:

lda \geq \max (1, n)

5: $ipiv (*)$ – Integer array Input

Note: the dimension of the array ipiv must be at least

\max (1, n)

On entry: details of the interchanges and the block structure of

D

, as returned by f07mdf.

6: $anorm$ – Real (Kind=nag_wp) Input

On entry: the

1

-norm of the original matrix

A

, which may be computed by calling f06rcf with its argument

norm ='1'

. anorm must be computed either before calling f07mdf or else from a copy of the original matrix

A

Constraint:

anorm \geq 0.0

7: $rcond$ – Real (Kind=nag_wp) Output

On exit: an estimate of the reciprocal of the condition number of

A

. rcond is set to zero if exact singularity is detected or the estimate underflows. If rcond is less than machine precision,

A

is singular to working precision.

8: $work (2 \times n)$ – Real (Kind=nag_wp) array Workspace

9: $iwork (n)$ – Integer array Workspace

10: $info$ – Integer Output

On exit:

info = 0

unless the routine detects an error (see Section 6).

6 Error Indicators and Warnings

$info < 0$: If $info = - i$ , argument $i$ had an illegal value. An explanatory message is output, and execution of the program is terminated.

7 Accuracy

The computed estimate rcond is never less than the true value

ρ

, and in practice is nearly always less than

10 ρ

, although examples can be constructed where rcond is much larger.

8 Parallelism and Performance

f07mgf makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.

Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this routine. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

A call to f07mgf involves solving a number of systems of linear equations of the form

A x = b

; the number is usually

4

5

and never more than

11

. Each solution involves approximately

2 n^{2}

floating-point operations but takes considerably longer than a call to f07mef with one right-hand side, because extra care is taken to avoid overflow when

A

is approximately singular.

The complex analogues of this routine are f07muf for Hermitian matrices and f07nuf for symmetric matrices.

10 Example

This example estimates the condition number in the

1

-norm (or

\infty

-norm) of the matrix

A

, where

A = (\begin{matrix} 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 \end{matrix}) .

Here

A

is symmetric indefinite and must first be factorized by f07mdf. The true condition number in the

1

-norm is

75.68

f07mg: FL CL CPP AD

NAG FL Interfacef07mgf (dsycon)

▸▿ Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

NAG FL Interface
f07mgf (dsycon)