Latent Variable Models in Heterogeneous Spaces for Observations of Mixed Types

DOI10.1080/03610920802155486zbMath1292.62091OpenAlexW2043856695MaRDI QIDQ5495083

Ernest Fokoué

Publication date: 30 July 2014

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920802155486

zbMATH Keywords

Monte CarloEM algorithmfactor analysisconditional independencegeneralized linear modellatent variable modelsfinite mixturesFisher scorenon Gaussian observations

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Measures of association (correlation, canonical correlation, etc.) (62H20) Generalized linear models (logistic models) (62J12)

Uses Software

• Fahrmeir

Cites Work

• Multivariate statistical modelling based on generalized linear models. With contributions by Wolfgang Hennevogl
• Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm
• Latent Variable Models with Mixed Continuous and Polytomous Data

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