Tuesday, November 26, 2013, 14:30 to 15:30, Grand Amphithéatre, INRIA Montbonnot
Seminar by Geoff McLachlan, Department of Mathematics, University of Queensland, Australia
Abstract. Non-normal mixture distributions have received increasing attention in recent years. Finite mixtures of multivariate skew symmetric distributions, in particular, the skew normal and skew $t$-mixture models, are emerging as a promising extension to the traditional normal and $t$-mixture modelling. Most of these parametric families of skew symmetric distributions are closely related. In this talk, we give a brief overview of various existing proposals for multivariate skew distributions. We compare the relative performance of restricted and unrestricted skew mixture models in clustering and density estimation on some real datasets. We also compare their performance with some mixtures having other non-normal component distributions.
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