A dual subspace parsimonious mixture of matrix normal distributions

Alex Sharp (), Glen Chalatov and Ryan P. Browne
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Alex Sharp: University of Waterloo
Glen Chalatov: University of Waterloo
Ryan P. Browne: University of Waterloo

Advances in Data Analysis and Classification, 2023, vol. 17, issue 3, No 10, 822 pages

Abstract: Abstract We present a parsimonious dual-subspace clustering approach for a mixture of matrix-normal distributions. By assuming certain principal components of the row and column covariance matrices are equally important, we express the model in fewer parameters without sacrificing discriminatory information. We derive update rules for an ECM algorithm and set forth necessary conditions to ensure identifiability. We use simulation to demonstrate parameter recovery, and we illustrate the parsimony and competitive performance of the model through two data analyses.

Keywords: Model-based clustering; Subspace projection; EM algorithm; Three-way data; 62H30 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11634-022-00526-2

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