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Title: Some skew distributions useful in model-based clustering Authors:  Sharon Lee - University of Adelaide (Australia)
Geoffrey McLachlan - University of Queensland (Australia) [presenting]
Abstract: The literature on non-normal model-based clustering has continued to grow in recent years. The non-normal models often take the form of a mixture of component densities that offer a high degree of flexibility in distributional shapes. They handle skewness in different ways, most typically by introducing latent skewing variable(s), while some others consider marginal transformations of the original variable(s). We focus on various scale mixtures of fundamental skew-symmetric distributions and methods for their fitting via the EM algorithm.