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Numerical methods for solving linear least squares problems

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Abstract

A common problem in a Computer Laboratory is that of finding linear least squares solutions. These problems arise in a variety of areas and in a variety of contexts. Linear least squares problems are particularly difficult to solve because they frequently involve large quantities of data, and they are ill-conditioned by their very nature. In this paper, we shall consider stable numerical methods for handling these problems. Our basic tool is a matrix decomposition based on orthogonal Householder transformations.

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Authors and Affiliations

  1. Computation Center, Stanford University, 94305, Stanford, California, USA

    G. Golub

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  1. G. Golub
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Reproduction in Whole or in Part is permitted for any Purpose of the United States government. This report was supported in part by Office of Naval Research Contract Nonr-225(37) (NR 044-11) at Stanford University.

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Golub, G. Numerical methods for solving linear least squares problems. Numer. Math. 7, 206–216 (1965). https://doi.org/10.1007/BF01436075

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  • DOI: https://doi.org/10.1007/BF01436075

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