Subset selection in multiple linear regression: a new mathematical programming approach

Subset selection in multiple linear regression: a new mathematical programming approach

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Article ID: iaor2006393
Country: United Kingdom
Volume: 49
Issue: 1
Start Page Number: 155
End Page Number: 167
Publication Date: Aug 2005
Journal: Computers & Industrial Engineering
Authors: , ,
Keywords: programming: mathematical, statistics: multivariate
Abstract:

A new mathematical programming model is proposed to address the subset selection problem in multiple linear regression where the objective is to select a minimal subset of predictor variables without sacrificing any explanatory power. A parametric solution of this model yields a number of efficient subsets. To obtain this solution, an optimal or one of two heuristic algorithms is repeatedly used. The subsets generated are compared to ones generated by several standard procedures. The results suggest that the new approach finds subsets that compare favorably against the standard procedures in terms of the generally accepted measure: adjusted R2.

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