GGLSE: 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 generalized RQ factorization of the matrices (B, A) given by B = (0 R)*Q, A = Z*T*Q. More...

Public Member Functions
	la_cgglse

	la_dgglse

	la_qgglse

	la_sgglse

	la_wgglse

	la_zgglse

Detailed Description

GGLSE: 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 generalized RQ factorization of the matrices (B, A) given by B = (0 R)*Q, A = Z*T*Q.

Member Function/Subroutine Documentation

◆ la_cgglse()

la_lapack::gglse::la_cgglse

◆ la_dgglse()

la_lapack::gglse::la_dgglse

◆ la_qgglse()

la_lapack::gglse::la_qgglse

◆ la_sgglse()

la_lapack::gglse::la_sgglse

◆ la_wgglse()

la_lapack::gglse::la_wgglse

◆ la_zgglse()

la_lapack::gglse::la_zgglse

The documentation for this interface was generated from the following file:

la_lapack.F90

Public Member Functions