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NAG Toolbox: nag_lapack_dppequ (f07gf)

 Contents

    1  Purpose
    2  Syntax
    7  Accuracy
    9  Example

Purpose

nag_lapack_dppequ (f07gf) computes a diagonal scaling matrix S  intended to equilibrate a real n  by n  symmetric positive definite matrix A , stored in packed format, and reduce its condition number.

Syntax

[s, scond, amax, info] = f07gf(uplo, n, ap)
[s, scond, amax, info] = nag_lapack_dppequ(uplo, n, ap)

Description

nag_lapack_dppequ (f07gf) computes a diagonal scaling matrix S  chosen so that
sj=1 / ajj .  
This means that the matrix B  given by
B=SAS ,  
has diagonal elements equal to unity. This in turn means that the condition number of B , κ2B , is within a factor n  of the matrix of smallest possible condition number over all possible choices of diagonal scalings (see Corollary 7.6 of Higham (2002)).

References

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

Parameters

Compulsory Input Parameters

1:     uplo – string (length ≥ 1)
Indicates whether the upper or lower triangular part of A is stored in the array ap, as follows:
uplo='U'
The upper triangle of A is stored.
uplo='L'
The lower triangle of A is stored.
Constraint: uplo='U' or 'L'.
2:     n int64int32nag_int scalar
n, the order of the matrix A.
Constraint: n0.
3:     ap: – double array
The dimension of the array ap must be at least max1,n×n+1/2
The n by n symmetric matrix A, packed by columns.
More precisely,
  • if uplo='U', the upper triangle of A must be stored with element Aij in api+jj-1/2 for ij;
  • if uplo='L', the lower triangle of A must be stored with element Aij in api+2n-jj-1/2 for ij.
Only the elements of ap corresponding to the diagonal elements A are referenced.

Optional Input Parameters

None.

Output Parameters

1:     sn – double array
If info=0, s contains the diagonal elements of the scaling matrix S.
2:     scond – double scalar
If info=0, scond contains the ratio of the smallest value of s to the largest value of s. If scond0.1 and amax is neither too large nor too small, it is not worth scaling by S.
3:     amax – double scalar
maxaij. If amax is very close to overflow or underflow, the matrix A should be scaled.
4:     info int64int32nag_int scalar
info=0 unless the function detects an error (see Error Indicators and Warnings).

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.
   info>0
The _th diagonal element of A is not positive (and hence A cannot be positive definite).

Accuracy

The computed scale factors will be close to the exact scale factors.

Further Comments

The complex analogue of this function is nag_lapack_zppequ (f07gt).

Example

This example equilibrates the symmetric positive definite matrix A  given by
A = -4.16 -3.12×105 -0.56 -0.10 -3.12×105 -5.03×1010 -0.83×105 -1.18×105 -0.56 -0.83×105 -0.76 -0.34 -0.10 -1.18×105 -0.34 -1.18 .  
Details of the scaling factors and the scaled matrix are output.
function f07gf_example


fprintf('f07gf example results\n\n');

% Symmetric matrix A, upper triangular part packed in ap
uplo = 'U';
n  = int64(4);
ap = [4.16    ...
     -3.12e5  5.03e10  ...
      0.56   -0.83e4   0.76  ...
     -0.10    1.18e5   0.34  1.18];

% Scale
[s, scond, amax, info] = f07gf( ...
                                uplo, n, ap);

fprintf('scond = %8.1e, amax = %8.1e\n\n', scond, amax);
disp('Diagonal scaling factors');
fprintf('%10.1e',s);
fprintf('\n\n');

% Apply scalings
k = 0;
for i = 1:n
  for j = 1:i
    k = k + 1;
    asp(k) = s(i)*ap(k)*s(j);
  end
end

[ifail] = x04cc( ...
                 'Upper', 'Non-unit', n, asp, 'Scaled matrix');


f07gf example results

scond =  3.9e-06, amax =  5.0e+10

Diagonal scaling factors
   4.9e-01   4.5e-06   1.1e+00   9.2e-01

 Scaled matrix
             1          2          3          4
 1      1.0000    -0.6821     0.3149    -0.0451
 2                 1.0000    -0.0425     0.4843
 3                            1.0000     0.3590
 4                                       1.0000

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