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

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...

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Veröffentlicht in:British journal of mathematical & statistical psychology 2006-05, Vol.59 (1), p.133-150
Hauptverfasser: Ceulemans, Eva, Kiers, Henk A. L.
Format: Artikel
Sprache:eng
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Zusammenfassung: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.
ISSN:0007-1102
2044-8317
DOI:10.1348/000711005X64817