Maximum likelihood estimation of mixtures of factor analyzers

DOI10.1016/j.csda.2011.04.001zbMath1464.62134OpenAlexW1988754565MaRDI QIDQ1658325

Cinzia Viroli, Angela Montanari

Publication date: 14 August 2018

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

Full work available at URL: https://doi.org/10.1016/j.csda.2011.04.001

zbMATH Keywords

information matrixmodel-based clusteringmaximum likelihood

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Factor analysis and principal components; correspondence analysis (62H25) Estimation in multivariate analysis (62H12) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items

High-dimensional clustering via random projections ⋮ Mixtures of common \(t\)-factor analyzers for modeling high-dimensional data with missing values ⋮ Model-based clustering ⋮ Automated learning of mixtures of factor analysis models with missing information ⋮ Mixtures of common factor analyzers for high-dimensional data with missing information ⋮ The infinite Student's \(t\)-factor mixture analyzer for robust clustering and classification ⋮ A mixture of generalized hyperbolic factor analyzers ⋮ Robust clustering via mixtures of \(t\) factor analyzers with incomplete data

Uses Software

• R

Cites Work

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• Mixture Densities, Maximum Likelihood and the EM Algorithm
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• Dealing With Label Switching in Mixture Models
• Estimating the components of a mixture of normal distributions
• Variable Selection for Model-Based Clustering