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Chapter Contents
Chapter Introduction
NAG Toolbox

# NAG Toolbox: nag_lapack_zppcon (f07gu)

## Purpose

nag_lapack_zppcon (f07gu) estimates the condition number of a complex Hermitian positive definite matrix A$A$, where A$A$ has been factorized by nag_lapack_zpptrf (f07gr), using packed storage.

## Syntax

[rcond, info] = f07gu(uplo, n, ap, anorm)
[rcond, info] = nag_lapack_zppcon(uplo, n, ap, anorm)

## Description

nag_lapack_zppcon (f07gu) estimates the condition number (in the 1$1$-norm) of a complex Hermitian positive definite matrix A$A$:
 κ1(A) = ‖A‖1‖A − 1‖1 . $κ1(A)=‖A‖1‖A-1‖1 .$
Since A$A$ is Hermitian, κ1(A) = κ(A) = AA1${\kappa }_{1}\left(A\right)={\kappa }_{\infty }\left(A\right)={‖A‖}_{\infty }{‖{A}^{-1}‖}_{\infty }$.
Because κ1(A)${\kappa }_{1}\left(A\right)$ is infinite if A$A$ is singular, the function actually returns an estimate of the reciprocal of κ1(A)${\kappa }_{1}\left(A\right)$.

## 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

## Parameters

### Compulsory Input Parameters

1:     uplo – string (length ≥ 1)
Specifies how A$A$ has been factorized.
uplo = 'U'${\mathbf{uplo}}=\text{'U'}$
A = UHU$A={U}^{\mathrm{H}}U$, where U$U$ is upper triangular.
uplo = 'L'${\mathbf{uplo}}=\text{'L'}$
A = LLH$A=L{L}^{\mathrm{H}}$, where L$L$ is lower triangular.
Constraint: uplo = 'U'${\mathbf{uplo}}=\text{'U'}$ or 'L'$\text{'L'}$.
2:     n – int64int32nag_int scalar
n$n$, the order of the matrix A$A$.
Constraint: n0${\mathbf{n}}\ge 0$.
3:     ap( : $:$) – complex array
Note: the dimension of the array ap must be at least max (1,n × (n + 1) / 2)$\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}×\left({\mathbf{n}}+1\right)/2\right)$.
The Cholesky factor of A$A$ stored in packed form, as returned by nag_lapack_zpptrf (f07gr).
4:     anorm – double scalar
The 1$1$-norm of the original matrix A$A$, which may be computed by calling nag_blas_zlanhp (f06ud) with its parameter norm = '1'${\mathbf{norm}}=\text{'1'}$. anorm must be computed either before calling nag_lapack_zpptrf (f07gr) or else from a copy of the original matrix A$A$.
Constraint: anorm0.0${\mathbf{anorm}}\ge 0.0$.

None.

work rwork

### Output Parameters

1:     rcond – double scalar
An estimate of the reciprocal of the condition number of A$A$. rcond is set to zero if exact singularity is detected or the estimate underflows. If rcond is less than machine precision, A$A$ is singular to working precision.
2:     info – int64int32nag_int scalar
info = 0${\mathbf{info}}=0$ unless the function detects an error (see Section [Error Indicators and Warnings]).

## Error Indicators and Warnings

info = i${\mathbf{info}}=-i$
If info = i${\mathbf{info}}=-i$, parameter i$i$ had an illegal value on entry. The parameters are numbered as follows:
1: uplo, 2: n, 3: ap, 4: anorm, 5: rcond, 6: work, 7: rwork, 8: info.
It is possible that info refers to a parameter that is omitted from the MATLAB interface. This usually indicates that an error in one of the other input parameters has caused an incorrect value to be inferred.

## Accuracy

The computed estimate rcond is never less than the true value ρ$\rho$, and in practice is nearly always less than 10ρ$10\rho$, although examples can be constructed where rcond is much larger.

A call to nag_lapack_zppcon (f07gu) involves solving a number of systems of linear equations of the form Ax = b$Ax=b$; the number is usually 5$5$ and never more than 11$11$. Each solution involves approximately 8n2$8{n}^{2}$ real floating point operations but takes considerably longer than a call to nag_lapack_zpptrs (f07gs) with one right-hand side, because extra care is taken to avoid overflow when A$A$ is approximately singular.
The real analogue of this function is nag_lapack_dppcon (f07gg).

## Example

```function nag_lapack_zppcon_example
uplo = 'L';
n = int64(4);
ap = [1.797220075561143;
0.8401864749527325 + 1.068316577423342i;
1.057188279741849 - 0.467388502622712i;
0.233694251311356 - 1.391037210186643i;
1.316353439509685 + 0i;
-0.4701749470106329 + 0.3130658155999466i;
0.08335250923944192 + 0.03676071443037458i;
1.560392977137124 + 0i;
0.9359617337923402 + 0.9899692192815736i;
0.6603332973655893 + 0i];
anorm = 10.96735730690591;
[rcond, info] = nag_lapack_zppcon(uplo, n, ap, anorm)
```
```

rcond =

0.0066

info =

0

```
```function f07gu_example
uplo = 'L';
n = int64(4);
ap = [1.797220075561143;
0.8401864749527325 + 1.068316577423342i;
1.057188279741849 - 0.467388502622712i;
0.233694251311356 - 1.391037210186643i;
1.316353439509685 + 0i;
-0.4701749470106329 + 0.3130658155999466i;
0.08335250923944192 + 0.03676071443037458i;
1.560392977137124 + 0i;
0.9359617337923402 + 0.9899692192815736i;
0.6603332973655893 + 0i];
anorm = 10.96735730690591;
[rcond, info] = f07gu(uplo, n, ap, anorm)
```
```

rcond =

0.0066

info =

0

```