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Selecting among three-mode principal component models of different types and complexities: A numerical convex hull based method

Authors


Correspondence should be addressed to Eva Ceulemans, Department of Psychology, Tiensestraat 102, B-3000 Leuven, Belgium (e-mail: eva.ceulemans@psy.kuleuven.be).

Abstract

Several three-mode principal component models can be considered for the modelling of three-way, three-mode data, including the Candecomp/Parafac, Tucker3, Tucker2, and Tucker1 models. The following question then may be raised: given a specific data set, which of these models should be selected, and at what complexity (i.e. with how many components)? We address this question by proposing a numerical model selection heuristic based on a convex hull. Simulation results show that this heuristic performs almost perfectly, except for Tucker3 data arrays with at least one small mode and a relatively large amount of error.

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