NAME¶

SLAIC1 - applies one step of incremental condition estimation in its simplest version

SYNOPSIS¶

SUBROUTINE SLAIC1(

JOB, J, X, SEST, W, GAMMA, SESTPR, S, C )

INTEGER J, JOB REAL C, GAMMA, S, SEST, SESTPR REAL W( J ), X( J )

PURPOSE¶

SLAIC1 applies one step of incremental condition estimation in its simplest version: Let x, twonorm(x) = 1, be an approximate singular vector of an j-by-j lower triangular matrix L, such that
twonorm(L*x) = sest
Then SLAIC1 computes sestpr, s, c such that
the vector
[ s*x ]
xhat = [ c ]
is an approximate singular vector of
[ L 0 ]
Lhat = [ w' gamma ]
in the sense that
twonorm(Lhat*xhat) = sestpr.
Depending on JOB, an estimate for the largest or smallest singular value is computed.
Note that [s c]' and sestpr**2 is an eigenpair of the system
diag(sest*sest, 0) + [alpha gamma] * [ alpha ]
[ gamma ]
where alpha = x'*w.

ARGUMENTS¶

JOB (input) INTEGER

= 1: an estimate for the largest singular value is computed.
= 2: an estimate for the smallest singular value is computed.

J (input) INTEGER

Length of X and W

X (input) REAL array, dimension (J)

The j-vector x.

SEST (input) REAL

Estimated singular value of j by j matrix L

W (input) REAL array, dimension (J)

The j-vector w.

GAMMA (input) REAL

The diagonal element gamma.

SESTPR (output) REAL

Estimated singular value of (j+1) by (j+1) matrix Lhat.

S (output) REAL

Sine needed in forming xhat.

C (output) REAL

Cosine needed in forming xhat.