Robust mixtures of factor analysis models using the restricted multivariate skew-t distribution

DOI10.1177/1471082X17718119OpenAlexW2751948320MaRDI QIDQ5142194

Wan-Lun Wang, Sharon X. Lee, Tsung I. Lin, Geoffrey J. McLachlan

Publication date: 30 December 2020

Published in: Statistical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1177/1471082x17718119

zbMATH Keywords

robustnessmodel-based clusteringheavy tailsfactor analysismissing valuesrMST distribution

Mathematics Subject Classification ID

Statistics (62-XX)

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Robust clustering of multiply censored data via mixtures of \(t\) factor analyzers, On formulations of skew factor models: skew factors and/or skew errors, A flexible factor analysis based on the class of mean-mixture of normal distributions, A novel mixture model using the multivariate normal mean-variance mixture of Birnbaum-Saunders distributions and its application to extrasolar planets, A Bayesian multivariate mixture model for skewed longitudinal data with intermittent missing observations: An application to infant motor development, Model-based clustering via mixtures of unrestricted skew normal factor analyzers with complete and incomplete data, A robust factor analysis model based on the canonical fundamental skew-\(t\) distribution, Flexible factor model for handling missing data in supervised learning, Asymmetric clusters and outliers: mixtures of multivariate contaminated shifted asymmetric Laplace distributions, An evolutionary algorithm with crossover and mutation for model-based clustering, Mixtures of restricted skew-\(t\) factor analyzers with common factor loadings, Mixtures of factor analyzers with scale mixtures of fundamental skew normal distributions, An overview of skew distributions in model-based clustering, A skew factor analysis model based on the normal mean–variance mixture of Birnbaum–Saunders distribution

Uses Software

• UCI-ml
• AS 136

Cites Work

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