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QICID: 30510
Title: An Exact Algorithm for Hierarchically Well-Formulated Subsets in Second-Order Polynomial Regression
Copyright: ASQ; American Statistical Association
Author: Brusco, Michael J.; Steinley, Douglas; Cradit, J. Dennis
Organization: Department of Marketing, College of Business, Florida State University; Department of Psychological Sciences, University of Missouri–Columbia; College of Business, Southern Illinois University
Subject: Algorithm; Optimization; Regression; Variable selection;
Series: Technometrics, Vol. 51, No. 3, August 2009, pp. 306–315
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Abstract: [This abstract is based on the authors' abstract.]
A branch-and-bound algorithm is presented for the selection of the best hierarchically well-formulated subset in second-order polynomial regression. The algorithm is applied to a data set from the regression literature, and results are compared to a similar algorithm that does not impose the hierarchical constraints. Results indicate that the hierarchical constraints yield only a small penalty in explained variation.
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