A factorization method for the solution of constrained linear least squares problems allowing subsequent data changes

Summary In this paper we describe how to use Gram-Schmidt factorizations of Daniel et al. 1] to realize the method of 8] for solving linearly constrained linear least squares problems. The main advantage of using these factorizations is that it is relatively easy to take data changes into account, if necessary.The algorithm is compared numerically with two other codes, one of them published by Lawson and Hanson 3]. Further computational tests show the efficiency of the proposed methods, if a few data of the original problem are changed subsequently.This paper was sponsored by Deutsche Forschungsgemeinschaft, Bonn-Bad Godesberg