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Dual‐ and triple‐mode matrix approximation and regression modelling

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  • Stan Lipovetsky
  • W. Michael Conklin

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.

Suggested Citation

  • Stan Lipovetsky & W. Michael Conklin, 2003. "Dual‐ and triple‐mode matrix approximation and regression modelling," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 19(4), pages 291-301, October.
    • Handle: RePEc:wly:apsmbi:v:19:y:2003:i:4:p:291-301
    DOI: 10.1002/asmb.503
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