sgglse - solve the linear equality-constrained least squares (LSE) problem
SUBROUTINE SGGLSE( M, N, P, A, LDA, B, LDB, C, D, X, WORK, LDWORK, * INFO) INTEGER M, N, P, LDA, LDB, LDWORK, INFO REAL A(LDA,*), B(LDB,*), C(*), D(*), X(*), WORK(*)
SUBROUTINE SGGLSE_64( M, N, P, A, LDA, B, LDB, C, D, X, WORK, * LDWORK, INFO) INTEGER*8 M, N, P, LDA, LDB, LDWORK, INFO REAL A(LDA,*), B(LDB,*), C(*), D(*), X(*), WORK(*)
SUBROUTINE GGLSE( [M], [N], [P], A, [LDA], B, [LDB], C, D, X, [WORK], * [LDWORK], [INFO]) INTEGER :: M, N, P, LDA, LDB, LDWORK, INFO REAL, DIMENSION(:) :: C, D, X, WORK REAL, DIMENSION(:,:) :: A, B
SUBROUTINE GGLSE_64( [M], [N], [P], A, [LDA], B, [LDB], C, D, X, * [WORK], [LDWORK], [INFO]) INTEGER(8) :: M, N, P, LDA, LDB, LDWORK, INFO REAL, DIMENSION(:) :: C, D, X, WORK REAL, DIMENSION(:,:) :: A, B
#include <sunperf.h>
void sgglse(int m, int n, int p, float *a, int lda, float *b, int ldb, float *c, float *d, float *x, int *info);
void sgglse_64(long m, long n, long p, float *a, long lda, float *b, long ldb, float *c, float *d, float *x, long *info);
sgglse solves the linear equality-constrained least squares (LSE) problem:
minimize || c - A*x ||_2 subject to B*x = d
where A is an M-by-N matrix, B is a P-by-N matrix, c is a given M-vector, and d is a given P-vector. It is assumed that
P <= N <= M+P, and
rank(B) = P and rank( ( A ) ) = N.
( ( B ) )
These conditions ensure that the LSE problem has a unique solution, which is obtained using a GRQ factorization of the matrices B and A.
WORK(1)
returns the optimal LDWORK.
If LDWORK = -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 LDWORK is issued by XERBLA.
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.