Quotation Frühwirth-Schnatter, Sylvia, Pyne, Saumyadipta. 2010. Bayesian Inference for Finite Mixtures of Univariate and Multivariate Skew Normal and Skew-t Distributions. Biostatistics 11 317-336.


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Abstract

Skew-normal and skew-t distributions have proved to be useful for capturing skewness and kurtosis in data directly without transformation. Recently, finite mixtures of such distributions have been considered as a more general tool for handling heterogeneous data involving asymmetric behaviors across subpopulations. We consider such mixture models for both univariate as well as multivariate data. This allows robust modeling of high-dimensional multimodal and asymmetric data generated by popular biotechnological platforms such as flow cytometry. We develop Bayesian inference based on data augmentation and Markov chain Monte Carlo (MCMC) sampling. In addition to the latent allocations, data augmentation is based on a stochastic representation of the skew-normal distribution in terms of a random-effects model with truncated normal random effects. For finite mixtures of skew normals, this leads to a Gibbs sampling scheme that draws from standard densities only. This MCMC scheme is extended to mixtures of skew-t distributions based on representing the skew-t distribution as a scale mixture of skew normals. As an important application of our new method, we demonstrate how it provides a new computational framework for automated analysis of high-dimensional flow cytometric data. Using multivariate skew-normal and skew-t mixture models, we could model non-Gaussian cell populations rigorously and directly without transformation or projection to lower dimensions.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Biostatistics
Citation Index SCI
WU-Journal-Rating new FIN-A
Language English
Title Bayesian Inference for Finite Mixtures of Univariate and Multivariate Skew Normal and Skew-t Distributions
Volume 11
Year 2010
Page from 317
Page to 336
URL http://biostatistics.oxfordjournals.org/content/11/2/317.abstract

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Frühwirth-Schnatter, Sylvia (Details)
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Pyne, Saumyadipta
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