Clustering via Mixture Regression Models with Random Effects

Geoffrey J. McLachlan (), Shu Kay (Angus) Ng () and Kui Wang ()
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Geoffrey J. McLachlan: University of Queensland, Department of Mathematics & Institute for Moelcular Bioscience
Shu Kay (Angus) Ng: University Drive, School of Medicine, Griffith University
Kui Wang: University of Queensland, Department of Mathematics

A chapter in COMPSTAT 2008, 2008, pp 397-407 from Springer

Abstract: Abstract In this paper, we consider the use of mixtures of linear mixed models to cluster data which may be correlated and replicated and which may have covariates. For each cluster, a regression model is adopted to incorporate the covariates, and the correlation and replication structure in the data are specified by the inclusion of random effects terms. The procedure is illustrated in its application to the clustering of gene-expression profiles.

Keywords: correlated data; random effects; mixed linear models; gene profiles (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-7908-2084-3_33

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DOI: 10.1007/978-3-7908-2084-3_33

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