A finite mixture approach to joint clustering of individuals and multivariate discrete outcomes

DOI10.1080/00949655.2017.1322593zbMath1465.62121OpenAlexW2613294715MaRDI QIDQ5106920

Francesca Martella, Marco Alfo'

Publication date: 22 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2017.1322593

zbMATH Keywords

maximum likelihood estimationdiscrete datafinite mixturesjoint clustering

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (1)

Biclustering multivariate discrete longitudinal data

Uses Software

• UCI-ml
• BaySeq
• DEseq
• EDAseq
• BicAT
• biclust
• blockcluster
• BiGGEsTS
• EXPANDER

Cites Work

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