NAG Library Function Document

nag_dspcon (f07pgc)

void	nag_dspcon (Nag_OrderType order, Nag_UploType uplo, Integer n, const double ap[], const Integer ipiv[], double anorm, double rcond, NagError fail)

3 Description

nag_dspcon (f07pgc) 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 function actually returns an estimate of the reciprocal of

κ_{1} (A)

The function should be preceded by a call to nag_dsp_norm (f16rdc) to compute

{‖A‖}_{1}

and a call to nag_dsptrf (f07pdc) to compute the Bunch–Kaufman factorization of

A

. The function 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: order – Nag_OrderTypeInput

On entry: the order argument specifies the two-dimensional storage scheme being used, i.e., row-major ordering or column-major ordering. C language defined storage is specified by

order = Nag_RowMajor

. See Section 3.2.1.3 in the Essential Introduction for a more detailed explanation of the use of this argument.

Constraint:

order = Nag_RowMajor

Nag_ColMajor

2: uplo – Nag_UploTypeInput

On entry: specifies how

A

has been factorized.

$uplo = Nag_Upper$: $A = P U D U^{T} P^{T}$ , where $U$ is upper triangular.
$uplo = Nag_Lower$: $A = P L D L^{T} P^{T}$ , where $L$ is lower triangular.

Constraint:

uplo = Nag_Upper

Nag_Lower

3: n – IntegerInput

On entry:

n

, the order of the matrix

A

Constraint:

n \geq 0

4: ap[ $\dim$ ] – const doubleInput

Note: the dimension, dim, of the array ap must be at least

\max (1, n \times (n + 1) / 2)

On entry: the factorization of

A

stored in packed form, as returned by nag_dsptrf (f07pdc).

5: ipiv[ $\dim$ ] – const IntegerInput

Note: the dimension, dim, 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 nag_dsptrf (f07pdc).

6: anorm – doubleInput

On entry: the

1

-norm of the original matrix

A

, which may be computed by calling nag_dsp_norm (f16rdc) with its argument

norm = Nag_OneNorm

. anorm must be computed either before calling nag_dsptrf (f07pdc) or else from a copy of the original matrix

A

Constraint:

anorm \geq 0.0

7: rcond – double *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: fail – NagError *Input/Output

The NAG error argument (see Section 3.6 in the Essential Introduction).

6 Error Indicators and Warnings

NE_ALLOC_FAIL: Dynamic memory allocation failed.
NE_BAD_PARAM: On entry, argument $⟨value⟩$ had an illegal value.
NE_INT: On entry, $n = ⟨value⟩$ .
Constraint: $n \geq 0$ .
NE_INTERNAL_ERROR: An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
NE_REAL: On entry, $anorm = ⟨value⟩$ .
Constraint: $anorm \geq 0.0$ .

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

nag_dspcon (f07pgc) is not threaded by NAG in any implementation.

nag_dspcon (f07pgc) 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 Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

A call to nag_dspcon (f07pgc) 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 nag_dsptrs (f07pec) with one right-hand side, because extra care is taken to avoid overflow when

A

is approximately singular.

The complex analogues of this function are nag_zhpcon (f07puc) for Hermitian matrices and nag_zspcon (f07quc) 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, stored in packed form, and must first be factorized by nag_dsptrf (f07pdc). The true condition number in the

1

-norm is

75.68

NAG Library Function Documentnag_dspcon (f07pgc)

+− 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 Library Function Document

nag_dspcon (f07pgc)