120.
An iterative procedure is developed for reducing the rounding errors in the computed least squares solution to an overdetermined system of equations
Ax =
b, where
A is an
m ×
n matrix (
m n) of rank
n. The method relies on computing accurate residuals to a certain augmented system of linear equations, by using double precision accumulation of inner products. To determine the corrections, two methods are given, based on a matrix decomposition of
A obtained either by orthogonal Householder transformations or by a modified Gram-Schmidt orthogonalization. It is shown that the rate of convergence in the iteration is independent of the right hand side,
b, and depends linearly on the condition number, 2135;(
A), of the rectangular matrix
A. The limiting accuracy achieved will be approximately the same as that obtained by a double precision factorization.In a second part of this paper the case when
x is subject to linear constraints and/or
A has rank less than
n is covered. Here also ALGOL-programs embodying the derived algorithms will be given.This work was sponsored by the Swedish Natural Science Research Council.
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