slasq4 (l) - Linux Manuals

slasq4: computes an approximation TAU to the smallest eigenvalue using values of d from the previous transform

NAME

SLASQ4 - computes an approximation TAU to the smallest eigenvalue using values of d from the previous transform

SYNOPSIS

SUBROUTINE SLASQ4(
I0, N0, Z, PP, N0IN, DMIN, DMIN1, DMIN2, DN, DN1, DN2, TAU, TTYPE, G )

    
INTEGER I0, N0, N0IN, PP, TTYPE

    
REAL DMIN, DMIN1, DMIN2, DN, DN1, DN2, G, TAU

    
REAL Z( * )

PURPOSE

SLASQ4 computes an approximation TAU to the smallest eigenvalue using values of d from the previous transform. I0 (input) INTEGER

First index.
N0 (input) INTEGER

Last index.
Z (input) REAL array, dimension ( 4*N )

Z holds the qd array.
PP (input) INTEGER

PP=0 for ping, PP=1 for pong.
NOIN (input) INTEGER

The value of N0 at start of EIGTEST.
DMIN (input) REAL

Minimum value of d.
DMIN1 (input) REAL

Minimum value of d, excluding D( N0 ).
DMIN2 (input) REAL

Minimum value of d, excluding D( N0 ) and D( N0-1 ). DN (input) REAL

d(N)
DN1 (input) REAL

d(N-1)
DN2 (input) REAL

d(N-2)
TAU (output) REAL

This is the shift.
TTYPE (output) INTEGER

Shift type.
G (input/output) REAL

G is passed as an argument in order to save its value between
calls to SLASQ4.

FURTHER DETAILS

Pages related to slasq4

  • slasq4 (3)
  • slasq1 (l) - computes the singular values of a real N-by-N bidiagonal matrix with diagonal D and off-diagonal E
  • slasq2 (l) - computes all the eigenvalues of the symmetric positive definite tridiagonal matrix associated with the qd array Z to high relative accuracy are computed to high relative accuracy, in the absence of denormalization, underflow and overflow
  • slasq3 (l) - checks for deflation, computes a shift (TAU) and calls dqds
  • slasq5 (l) - computes one dqds transform in ping-pong form, one version for IEEE machines another for non IEEE machines
  • slasq6 (l) - computes one dqd (shift equal to zero) transform in ping-pong form, with protection against underflow and overflow
  • slas2 (l) - computes the singular values of the 2-by-2 matrix [ F G ] [ 0 H ]
  • slascl (l) - multiplies the M by N real matrix A by the real scalar CTO/CFROM
  • slascl2 (l) - performs a diagonal scaling on a vector
  • slasd0 (l) - a divide and conquer approach, SLASD0 computes the singular value decomposition (SVD) of a real upper bidiagonal N-by-M matrix B with diagonal D and offdiagonal E, where M = N + SQRE