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