A graph approach to generate all possible regression submodels

Gatu, C. and Yanev, P.I. and Kontoghiorghes, Erricos J. (2007) A graph approach to generate all possible regression submodels. Computational Statistics & Data Analysis 52 (2), 799 - 815. ISSN 0167-9473.

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Official URL: http://dx.doi.org/10.1016/j.csda.2007.02.018

Abstract

A regression graph to enumerate and evaluate all possible subset regression models is introduced. The graph is a generalization of a regression tree. All the spanning trees of the graph are minimum spanning trees and provide an optimal computational procedure for generating all possible submodels. Each minimum spanning tree has a different structure and characteristics. An adaptation of a branch-and-bound algorithm which computes the best-subset models using the regression graph framework is proposed. Experimental results and comparison with an existing method based on a regression tree are presented and discussed.

Metadata

Item Type:	Article
Keyword(s) / Subject(s):	Graphs, regression trees, model selection, combinatorial algorithms
School:	School of Business, Economics & Informatics > Computer Science and Information Systems
Depositing User:	Administrator
Date Deposited:	08 Aug 2011 13:04
Last Modified:	17 Apr 2013 12:21
URI:	https://eprints.bbk.ac.uk/id/eprint/3967

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