title: Simultaneous Component Analysis by Means of Tucker3.
abstract: A new model for simultaneous component analysis (SCA) is introduced that contains the existing SCA models with common loading matrix as special cases. The new SCA-T3 model is a multi-set generalization of the Tucker3 model for component analysis of three-way data. For each mode (observational units, variables, sets) a different number of components can be chosen and the obtained solution can be rotated without loss of fit to facilitate interpretation. SCA-T3 can be fitted on centered multi-set data and also on the corresponding covariance matrices. For this purpose, alternating least squares algorithms are derived. SCA-T3 is evaluated in a simulation study, and its practical merits are demonstrated for several benchmark datasets.
authors.affiliation: Group Science, Engineering and Technology, KU Leuven - Kulak, E. Sabbelaan 53, 8500, Kortrijk, Belgium. alwin.stegeman@kuleuven.be.|Department of Electrical Engineering (ESAT), KU Leuven, Kasteelpark Arenberg 10, 3001, Leuven, Belgium. alwin.stegeman@kuleuven.be.
authors.forename: Alwin
authors.identifier: 0000-0003-3385-2560
authors.initials: A
authors.lastname: Stegeman
mesh_terms: D000339:Affect; D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005163:Factor Analysis, Statistical; D006801:Humans; D007360:Intelligence; D007361:Intelligence Tests; D016018:Least-Squares Analysis; D016013:Likelihood Functions; D009010:Monte Carlo Method; D010300:Parkinson Disease / Q000523:psychology; D012959:Socioeconomic Factors
keywords: multi-set data; parafac; rotation; simultaneous components analysis; tucker