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NAME
SGGGLM - solve a generalized linear regression model (GLM)
problem
SYNOPSIS
SUBROUTINE SGGGLM( N, M, P, A, LDA, B, LDB, D, X, Y, WORK,
LWORK, INFO )
INTEGER INFO, LDA, LDB, LWORK, M, N, P
REAL A( LDA, * ), B( LDB, * ), D( * ), WORK( *
), X( * ), Y( * )
PURPOSE
SGGGLM solves a generalized linear regression model (GLM)
problem:
minimize y'*y subject to d = A*x + B*y
x,y
using a generalized QR factorization of A and B, where A is
an N-by-M matrix, B is a given N-by-P matrix, and d is a
given N vector. It is also assumed that M <= N <= M+P and
rank(A) = M and rank([ A B ]) = N.
Under these assumptions, the constrained equation is always
consistent, and there is a unique solution x and a minimal
2-norm solution y.
In particular, if matrix B is square nonsingular, then the
problem GLM is equivalent to the following weighted linear
least squares problem
minimize || inv(B)*(b-A*x) ||
x
where ||.|| is vector 2-norm, and inv(B) denotes the inverse
of matrix B.
ARGUMENTS
N (input) INTEGER
The number of rows of the matrices A and B. N >= 0.
M (input) INTEGER
The number of columns of the matrix A. M >= 0.
P (input) INTEGER
The number of columns of the matrix B. P >= 0.
Assume that M <= N <= M+P.
A (input/output) REAL array, dimension (LDA,M)
On entry, the N-by-M matrix A. On exit, A is
destroyed.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(
1,N ).
B (input/output) REAL array, dimension (LDB,P)
On entry, the N-by-P matrix B. On exit, B is des-
troyed.
LDB (input) INTEGER
The leading dimension of the array B. LDB >= max(
1,N ).
D (input) REAL array, dimension (N)
On entry, D is the left hand side of the GLM equa-
tion. On exit, D is destroyed.
X (output) REAL array, dimension (M)
Y (output) REAL array, dimension (P) On exit,
X and Y are the solutions of the GLM problem.
WORK (workspace) 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 >=
M+P+max(N,M,P). For optimum performance, LWORK >=
M+P+max(N,M,P)*max(NB1,NB2), where NB1 is the
optimal blocksize for the QR factorization of an N-
by-M matrix A. NB2 is the optimal blocksize for the
RQ factorization of an N-by-P matrix B.
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal
value.