Clustering via Mixture Regression Models with Random Effects
Geoffrey John McLachlan, Shu‐Kay Ng, Kui Wang · 2008
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.