Dual‐ and triple‐mode matrix approximation and regression modelling

Stan Lipovetsky and W. Michael Conklin

Applied Stochastic Models in Business and Industry, 2003, vol. 19, issue 4, 291-301

Abstract: We propose a dual‐ and triple‐mode least squares for matrix approximation. This technique applied to the singular value decomposition produces the classical solution with a new interpretation. Applied to regression modelling, this approach corresponds to a regularized objective and yields a new solution with properties of a ridge regression. The results for regression are robust and suggest a convenient tool for the analysis and interpretation of the model coefficients. Numerical results are given for a marketing research data set. Copyright © 2003 John Wiley & Sons, Ltd.

Date: 2003
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https://doi.org/10.1002/asmb.503

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Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmbi:v:19:y:2003:i:4:p:291-301

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