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An alternating least squares method for the weighted approximation of a symmetric matrix

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Abstract

Bailey and Gower examined the least squares approximationC to a symmetric matrixB, when the squared discrepancies for diagonal elements receive specific nonunit weights. They focussed on mathematical properties of the optimalC, in constrained and unconstrained cases, rather than on how to obtainC for any givenB. In the present paper a computational solution is given for the case whereC is constrained to be positive semidefinite and of a fixed rankr or less. The solution is based on weakly constrained linear regression analysis.

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Authors and Affiliations

  1. Department of Psychology, University of Groningen, Grote Kruisstraat 2/1, 9712 TS, Groningen, The Netherlands

    Jos M. F. Berge & Henk A. L. Kiers

Authors
  1. Jos M. F. Berge
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  2. Henk A. L. Kiers
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The authors are obliged to John C. Gower for stimulating this research.

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Berge, J.M.F., Kiers, H.A.L. An alternating least squares method for the weighted approximation of a symmetric matrix. Psychometrika 58, 115–118 (1993). https://doi.org/10.1007/BF02294475

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  • DOI: https://doi.org/10.1007/BF02294475

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