Stable and visualizable Gaussian parsimonious clustering models

DOI10.1007/s11222-013-9413-5zbMath1332.62199OpenAlexW2012084096MaRDI QIDQ260986

Christophe Biernacki, Alexandre Lourme

Publication date: 22 March 2016

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

Full work available at URL: https://doi.org/10.1007/s11222-013-9413-5

zbMATH Keywords

correlationEM algorithmmaximum likelihoodstandard deviationfaithful projectionunit independence

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (9)

Multivariate response and parsimony for Gaussian cluster-weighted models ⋮ High-dimensional clustering via random projections ⋮ Unifying data units and models in (co-)clustering ⋮ Group-wise shrinkage estimation in penalized model-based clustering ⋮ Model-based clustering with determinant-and-shape constraint ⋮ Variable selection methods for model-based clustering ⋮ Multivariate hidden Markov regression models: random covariates and heavy-tailed distributions ⋮ Model-based clustering with sparse covariance matrices ⋮ On comparative study of clustering using finite mixture of non-Gaussian distributions

Uses Software

• mclust
• R
• MASS (R)
• Mixmod
• PGMM

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