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A stable method for solving certain constrained least squares problems

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Abstract

This paper presents a feasible descent algorithm for solving certain constrained least squares problems. These problems are specially structured quadratic programming problems with positive semidefinite Hessian matrices that are allowed to be singular. The algorithm generates a finite sequence of subproblems that are solved using the numerically stable technique of orthogonal factorization with reorthogonalization and Given's transformation updating.

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Authors and Affiliations

  1. Claremont Men's College, Claremont, CA., USA

    Robert Mifflin

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  1. Robert Mifflin
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Additional information

This material is based upon work supported by the National Science Foundation under Grant No. MCS 78-06716 and by the International Institute for Applied Systems Analysis.

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Mifflin, R. A stable method for solving certain constrained least squares problems. Mathematical Programming 16, 141–158 (1979). https://doi.org/10.1007/BF01582105

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  • DOI: https://doi.org/10.1007/BF01582105

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