Clustering via Mixture Regression Models with Random Effects
Author(s)
McLachlan, Geoffrey J
Ng, Sbu Kay Angus
Wang, Kui
Griffith University Author(s)
Year published
2008
Metadata
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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.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.
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Conference Title
COMPSTAT 2008: PROCEEDINGS IN COMPUTATIONAL STATISTICS