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.
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.
|Keyword(s) / Subject(s):||Graphs, regression trees, model selection, combinatorial algorithms|
|School:||Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems|
|Date Deposited:||08 Aug 2011 13:04|
|Last Modified:||17 Apr 2013 12:21|
Additional statistics are available via IRStats2.