Some Computational Procedures for the Best Subset Problem

In an earlier paper, Garside (1965) gave an algorithm for calculating all subsets in multiple-regression analysis, thereby obtaining the subset of a given size that minimized the minimum residual sum of squares. This paper develops further the facilities in the earlier algorithm and introduces a new...

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Veröffentlicht in:	Applied Statistics 1971-01, Vol.20 (1), p.8-15
1. Verfasser:	Garside, M. J.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied statistics Induced substructures Integers Linear regression Multiple regression Regression analysis Vertices
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description	In an earlier paper, Garside (1965) gave an algorithm for calculating all subsets in multiple-regression analysis, thereby obtaining the subset of a given size that minimized the minimum residual sum of squares. This paper develops further the facilities in the earlier algorithm and introduces a new algorithm which, although slightly restrictive, is very much faster in execution.
doi_str_mv	10.2307/2346626
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source	Periodicals Index Online; JSTOR Mathematics & Statistics; EBSCOhost Business Source Complete; JSTOR Archive Collection A-Z Listing
subjects	Algorithms Applied statistics Induced substructures Integers Linear regression Multiple regression Regression analysis Vertices
title	Some Computational Procedures for the Best Subset Problem
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