Dual‐ and triple‐mode matrix approximation and regression modelling
Stan Lipovetsky, W. Michael Conklin · Applied Stochastic Models in Business and Industry · 2003
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.