Clustering multivariate data using factor analytic Bayesian mixtures with an unknown number of components

DOI10.1007/s11222-019-09891-zzbMath1436.62280arXiv1906.00348OpenAlexW2970325798WikidataQ127280074 ScholiaQ127280074MaRDI QIDQ140405

Panagiotis Papastamoulis

Publication date: 27 August 2019

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1906.00348

zbMATH Keywords

factor analysismixture modelMCMC

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Factor analysis and principal components; correspondence analysis (62H25) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (3)

A data-driven reversible jump for estimating a finite mixture of regression models ⋮ On the identifiability of Bayesian factor analytic models ⋮ fabMix

Uses Software

• mclust
• R
• UCI-ml
• CODA
• PGMM
• foreach
• Rcpp
• RcppArmadillo
• doParallel
• Label.switching
• BayesBinMix
• doRNG

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