sgelsd(3)

NAME

SGELSD - compute the minimum-norm solution to a real lin
ear least squares problem

SYNOPSIS

SUBROUTINE  SGELSD(  M, N, NRHS, A, LDA, B, LDB, S, RCOND,
RANK, WORK, LWORK, IWORK, INFO )
    INTEGER        INFO, LDA, LDB, LWORK, M, N, NRHS, RANK
    REAL           RCOND
    INTEGER        IWORK( * )
    REAL           A( LDA, * ), B( LDB, * ), S( * ), WORK(
* )

PURPOSE

SGELSD computes the minimum-norm solution to a real linear
least squares problem: minimize 2-norm(| b - A*x |)
using the singular value decomposition (SVD) of A. A is an
M-by-N matrix which may be rank-deficient.
Several right hand side vectors b and solution vectors x
can be handled in a single call; they are stored as the columns
of the M-by-NRHS right hand side matrix B and the N-by-NRHS solu
tion matrix X.
The problem is solved in three steps:
(1) Reduce the coefficient matrix A to bidiagonal form
with
Householder transformations, reducing the original
problem
into a "bidiagonal least squares problem" (BLS)
(2) Solve the BLS using a divide and conquer approach.
(3) Apply back all the Householder tranformations to solve
the original least squares problem.
The effective rank of A is determined by treating as zero
those singular values which are less than RCOND times the largest
singular value.
The divide and conquer algorithm makes very mild assump
tions about floating point arithmetic. It will work on machines
with a guard digit in add/subtract, or on those binary machines
without guard digits which subtract like the Cray X-MP, Cray Y
MP, Cray C-90, or Cray-2. It could conceivably fail on hexadeci
mal or decimal machines without guard digits, but we know of
none.

ARGUMENTS

M (input) INTEGER
The number of rows of A. M >= 0.
N (input) INTEGER
The number of columns of A. N >= 0.
NRHS (input) INTEGER
The number of right hand sides, i.e., the number
of columns of the matrices B and X. NRHS >= 0.
A (input) REAL array, dimension (LDA,N)
On entry, the M-by-N matrix A. On exit, A has
been destroyed.
LDA (input) INTEGER
The leading dimension of the array A. LDA >=
max(1,M).
B (input/output) REAL array, dimension (LDB,NRHS)
On entry, the M-by-NRHS right hand side matrix B.
On exit, B is overwritten by the N-by-NRHS solution matrix X. If
m >= n and RANK = n, the residual sum-of-squares for the solution
in the i-th column is given by the sum of squares of elements
n+1:m in that column.
LDB (input) INTEGER
The leading dimension of the array B. LDB >=
max(1,max(M,N)).
S (output) REAL array, dimension (min(M,N))
The singular values of A in decreasing order. The
condition number of A in the 2-norm = S(1)/S(min(m,n)).
RCOND (input) REAL
RCOND is used to determine the effective rank of
A. Singular values S(i) <= RCOND*S(1) are treated as zero. If
RCOND < 0, machine precision is used instead.
RANK (output) INTEGER
The effective rank of A, i.e., the number of sin
gular values which are greater than RCOND*S(1).
WORK (workspace/output) REAL array, dimension (LWORK)
On exit, if INFO = 0, WORK(1) returns the optimal
LWORK.
LWORK (input) INTEGER
The dimension of the array WORK. LWORK must be at
least 1. The exact minimum amount of workspace needed depends on
M, N and NRHS. As long as LWORK is at least 12*N + 2*N*SMLSIZ +
8*N*NLVL + N*NRHS + (SMLSIZ+1)**2, if M is greater than or equal
to N or 12*M + 2*M*SMLSIZ + 8*M*NLVL + M*NRHS + (SMLSIZ+1)**2, if
M is less than N, the code will execute correctly. SMLSIZ is re
turned by ILAENV and is equal to the maximum size of the subprob
lems at the bottom of the computation tree (usually about 25),
and NLVL = MAX( 0, INT( LOG_2( MIN( M,N )/(SMLSIZ+1) ) ) + 1 )
For good performance, LWORK should generally be larger.
If LWORK = -1, then a workspace query is assumed;
the routine only calculates the optimal size of the WORK array,
returns this value as the first entry of the WORK array, and no
error message related to LWORK is issued by XERBLA.
IWORK (workspace) INTEGER array, dimension (LIWORK)
LIWORK >= 3 * MINMN * NLVL + 11 * MINMN, where
MINMN = MIN( M,N ).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an ille
gal value.
> 0: the algorithm for computing the SVD failed
to converge; if INFO = i, i off-diagonal elements of an interme
diate bidiagonal form did not converge to zero.

FURTHER DETAILS

Based on contributions by
Ming Gu and Ren-Cang Li, Computer Science Division,
University of
California at Berkeley, USA
Osni Marques, LBNL/NERSC, USA
LAPACK version 3.0 15 June 2000
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