title: Selecting among three-mode principal component models of different types and complexities: a numerical convex hull based method.
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.
authors.affiliation: Katholieke Universiteit Leuven, Belgium. eva.ceulemans@psy.kuleuven.be
authors.forename: Eva
authors.initials: E
authors.lastname: Ceulemans
authors.forename: Henk A L
authors.initials: HA
authors.lastname: Kiers
mesh_terms: D006801:Humans; D008960:Models, Psychological; D008962:Models, Theoretical; D011584:Psychology / Q000706:statistics & numerical data*