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Finite mixture models and model-based clustering. (English) Zbl 1190.62121

Summary: Finite mixture models have a long history in statistics, having been used to model population heterogeneity, generalize distributional assumptions, and lately, for providing a convenient yet formal framework for clustering and classification. This paper provides a detailed review of mixture models and model-based clustering. Recent trends as well as open problems in this area are also discussed.

MSC:

62H30 Classification and discrimination; cluster analysis (statistical aspects)
65C60 Computational problems in statistics (MSC2010)

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