Solutions to Weighted Least Squares Problems by Modified Gram-Schmidt with Iterative Refinement

Abstract

A Fortran Implementation of an algorithm for solving weighted least squares problems by modified Gram-Schmidt with iterative refinement is described. The algorithm is one known to provide maximum accuracy in the case of ill-conditioned problems. The types of problems which can be solved include overdetermined and underdetermined systems of linear equations, and problems where the solution is subject to linear equality constraints. The covariance matrix of the solution vector is computed. © 1979, ACM. All rights reserved.