dlasq6 (l) - Linux Manuals

dlasq6: computes one dqd (shift equal to zero) transform in ping-pong form, with protection against underflow and overflow

NAME

DLASQ6 - computes one dqd (shift equal to zero) transform in ping-pong form, with protection against underflow and overflow

SYNOPSIS

SUBROUTINE DLASQ6(
I0, N0, Z, PP, DMIN, DMIN1, DMIN2, DN, DNM1, DNM2 )

    
INTEGER I0, N0, PP

    
DOUBLE PRECISION DMIN, DMIN1, DMIN2, DN, DNM1, DNM2

    
DOUBLE PRECISION Z( * )

PURPOSE

DLASQ6 computes one dqd (shift equal to zero) transform in ping-pong form, with protection against underflow and overflow.

ARGUMENTS

I0 (input) INTEGER
First index.
N0 (input) INTEGER
Last index.
Z (input) DOUBLE PRECISION array, dimension ( 4*N )
Z holds the qd array. EMIN is stored in Z(4*N0) to avoid an extra argument.
PP (input) INTEGER
PP=0 for ping, PP=1 for pong.
DMIN (output) DOUBLE PRECISION
Minimum value of d. DMIN1 (output) DOUBLE PRECISION Minimum value of d, excluding D( N0 ). DMIN2 (output) DOUBLE PRECISION Minimum value of d, excluding D( N0 ) and D( N0-1 ).
DN (output) DOUBLE PRECISION
d(N0), the last value of d.
DNM1 (output) DOUBLE PRECISION
d(N0-1).
DNM2 (output) DOUBLE PRECISION
d(N0-2).

Pages related to dlasq6

  • dlasq6 (3)
  • dlasq1 (l) - computes the singular values of a real N-by-N bidiagonal matrix with diagonal D and off-diagonal E
  • dlasq2 (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
  • dlasq3 (l) - checks for deflation, computes a shift (TAU) and calls dqds
  • dlasq4 (l) - computes an approximation TAU to the smallest eigenvalue using values of d from the previous transform
  • dlasq5 (l) - computes one dqds transform in ping-pong form, one version for IEEE machines another for non IEEE machines
  • dlas2 (l) - computes the singular values of the 2-by-2 matrix [ F G ] [ 0 H ]
  • dlascl (l) - multiplies the M by N real matrix A by the real scalar CTO/CFROM
  • dlascl2 (l) - performs a diagonal scaling on a vector
  • dlasd0 (l) - a divide and conquer approach, DLASD0 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