A hierarchical mixture model for clustering three-way data sets

DOI10.1016/j.csda.2006.08.005zbMath1445.62154OpenAlexW2102321880MaRDI QIDQ1020215

Jeroen K. Vermunt

Publication date: 29 May 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://research.tilburguniversity.edu/en/publications/1660b3a5-5024-4061-a07d-22c702302317

zbMATH Keywords

EM algorithmlongitudinal dataclusteringfinite mixture modelthree-way datamultilevel latent class model

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (16)

Constrained multilevel latent class models for the analysis of three-way three-mode binary data ⋮ Model based clustering of customer choice data ⋮ A hierarchical modeling approach for clustering probability density functions ⋮ Clustering financial time series: new insights from an extended hidden Markov model ⋮ A new zero-inflated negative binomial methodology for latent category identification ⋮ A dimensionally reduced finite mixture model for multilevel data ⋮ Modal clustering of matrix-variate data ⋮ Least-squares bilinear clustering of three-way data ⋮ Biclustering multivariate discrete longitudinal data ⋮ Unnamed Item ⋮ Finite mixtures of matrix normal distributions for classifying three-way data ⋮ Testing the equality of matrix distributions ⋮ Clustering Discrete Choice Data ⋮ Long-term developments of respondent financial product portfolios in the EU: a multilevel latent class analysis ⋮ Editorial: Advances in mixture models ⋮ Latent mixture modeling for clustered data

Uses Software

• Latent GOLD

Cites Work

• Latent class models for classification
• Constrained latent class analysis of three-way three-mode data
• Fitting a mixture model to three-mode three-way data with missing information
• Fitting a mixture model to three-mode three-way data with categorical and continuous variables
• Bayesian Detection of Clusters and Discontinuities in Disease Maps
• Exploratory latent structure analysis using both identifiable and unidentifiable models
• A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains
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