Beyond principal component analysis: A trilinear decomposition model and least squares estimation

DOI10.1007/BF02294505zbMath0776.62051MaRDI QIDQ1205775

Pham Dinh Tuan, Joachim Möcks

Publication date: 1 April 1993

Published in: Psychometrika (Search for Journal in Brave)

zbMATH Keywords

consistencyasymptotic normalityfactor analysisprincipal componentsmultidimensional scalingleast squares estimatorstrilinear decompositionbilinear decompositionevoked brain potential dataloadings matrixscores matrixthree-mode data

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25)

Related Items (1)

ECOPICA: empirical copula-based independent component analysis

Uses Software

• PARAFAC

Cites Work

• Unnamed Item
• More factors than subjects, tests and treatments: An indeterminacy theorem for canonical decomposition and individual differences scaling
• Three-way arrays: rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics
• Analysis of individual differences in multidimensional scaling via an \(n\)-way generalization of ``Eckart-Young decomposition
• Linear Statistical Inference and its Applications

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