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We show how the expectation-maximization (EM) algorithm can be applied exactly for the fitting of mixtures of general multivariate skew t (MST) distributions, eliminating the need for computationally… (More)
Finite mixture models are being increasingly used to model the distributions of a wide variety of random phenomena and to cluster data sets. In this paper, we focus on the use of normal mixture… (More)
There is increasing interest in the use of diagnostic rules based on microarray data. These rules are formed by considering the expression levels of thousands of genes in tissue samples taken on… (More)
In this paper use consider the problem of providing standard errors of the component means in normal mixture models tted to univariate or multi-variate data by maximumlikelihood via the EM algorithm.… (More)
False discovery rate (FDR) control is important in multiple testing scenarios that are common in neuroimaging experiments, and p-values from such experiments may often arise from some discretely… (More)
Recently, observed departures from the classical Gaussian mixture model in real datasets motivated the introduction of mixtures of skew t , and remarkably widened the application of model based… (More)