Integer, Intent (In)	::	n, ipiv(*)
Integer, Intent (Out)	::	iwork(n), info
Real (Kind=nag_wp), Intent (In)	::	dl(), d(), du(), du2(), anorm
Real (Kind=nag_wp), Intent (Out)	::	rcond, work(2*n)
Character (1), Intent (In)	::	norm

C Header Interface

#include <nag.h>

void	f07cgf_ (const char norm, const Integer n, const double dl[], const double d[], const double du[], const double du2[], const Integer ipiv[], const double anorm, double rcond, double work[], Integer iwork[], Integer *info, const Charlen length_norm)

The routine may be called by the names f07cgf, nagf_lapacklin_dgtcon or its LAPACK name dgtcon.

3 Description

f07cgf should be preceded by a call to f07cdf, which uses Gaussian elimination with partial pivoting and row interchanges to factorize the matrix

A

A = P L U,

where

P

is a permutation matrix,

L

is unit lower triangular with at most one nonzero subdiagonal element in each column, and

U

is an upper triangular band matrix, with two superdiagonals. f07cgf then utilizes the factorization to estimate either

{‖A^{- 1}‖}_{1}

{‖A^{- 1}‖}_{\infty}

, from which the estimate of the reciprocal of the condition number of

A

1 / κ (A)

is computed as either

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

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

1 / κ (A)

is returned, rather than

κ (A)

, since when

A

is singular

κ (A)

is infinite.

Note that

κ_{\infty} (A) = κ_{1} (A^{T})

4 References

Higham N J (2002) Accuracy and Stability of Numerical Algorithms (2nd Edition) SIAM, Philadelphia

5 Arguments

1: $norm$ – Character(1) Input

On entry: specifies the norm to be used to estimate

κ (A)

$norm ='1'$ or $'O'$: Estimate $κ_{1} (A)$ .
$norm ='I'$: Estimate $κ_{\infty} (A)$ .

Constraint:

norm ='1'

'O'

'I'

2: $n$ – Integer Input

On entry:

n

, the order of the matrix

A

Constraint:

n \geq 0

3: $dl (*)$ – Real (Kind=nag_wp) array Input

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

\max (1, n - 1)

On entry: must contain the

(n - 1)

multipliers that define the matrix

L

of the

L U

factorization of

A

4: $d (*)$ – Real (Kind=nag_wp) array Input

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

\max (1, n)

On entry: must contain the

n

diagonal elements of the upper triangular matrix

U

from the

L U

factorization of

A

5: $du (*)$ – Real (Kind=nag_wp) array Input

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

\max (1, n - 1)

On entry: must contain the

(n - 1)

elements of the first superdiagonal of

U

6: $du2 (*)$ – Real (Kind=nag_wp) array Input

Note: the dimension of the array du2 must be at least

\max (1, n - 2)

On entry: must contain the

(n - 2)

elements of the second superdiagonal of

U

7: $ipiv (*)$ – Integer array Input

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

\max (1, n)

On entry: must contain the

n

pivot indices that define the permutation matrix

P

. At the

i

th step, row

i

of the matrix was interchanged with row

ipiv (i)

, and

ipiv (i)

must always be either

i

(i + 1)

ipiv (i) = i

indicating that a row interchange was not performed.

8: $anorm$ – Real (Kind=nag_wp) Input

On entry: if

norm ='1'

'O'

, the

1

-norm of the original matrix

A

norm ='I'

, the

\infty

-norm of the original matrix

A

anorm may be computed by calling f06rnf with the same value for the argument norm.

anorm must be computed either before calling f07cdf or else from a copy of the original matrix

A

(see Section 10).

Constraint:

anorm \geq 0.0

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

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

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

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

12: $info$ – 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

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.

8 Parallelism and Performance

f07cgf 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

The condition number estimation typically requires between four and five solves and never more than eleven solves, following the factorization. The total number of floating-point operations required to perform a solve is proportional to

n

The complex analogue of this routine is f07cuf.

10 Example

This example estimates the condition number in the

1

-norm of the tridiagonal matrix

A

given by

A = (\begin{array}{r} 3.0 & 2.1 & 0 & 0 & 0 \\ 3.4 & 2.3 & - 1.0 & 0 & 0 \\ 0 & 3.6 & - 5.0 & 1.9 & 0 \\ 0 & 0 & 7.0 & - 0.9 & 8.0 \\ 0 & 0 & 0 & - 6.0 & 7.1 \end{array}) .

Interfaces: FL CL AD

NAG FL Interface Introduction

F07 (Lapacklin) Chapter Contents

F07 (Lapacklin) Chapter Introduction

f07cg: FL CL AD

NAG FL Interfacef07cgf (dgtcon)

▸▿ 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
f07cgf (dgtcon)