SCALE MIXTURES DISTRIBUTIONS IN STATISTICAL MODELLING

S.T. Boris Choy, Jennifer S.K. Chan

doi:10.1111/j.1467-842x.2008.00504.x

SCALE MIXTURES DISTRIBUTIONS IN STATISTICAL MODELLING

DOI Web Site Web Site 被引用文献1件

書誌事項

公開日: 2008-06

権利情報

http://onlinelibrary.wiley.com/termsAndConditions#vor

DOI

10.1111/j.1467-842x.2008.00504.x

公開者: Wiley

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説明

<jats:title>Summary</jats:title><jats:p>This paper presents two types of symmetric scale mixture probability distributions which include the normal, Student t, Pearson Type VII, variance gamma, exponential power, uniform power and generalized t (GT) distributions. Expressing a symmetric distribution into a scale mixture form enables efficient Bayesian Markov chain Monte Carlo (MCMC) algorithms in the implementation of complicated statistical models. Moreover, the mixing parameters, a by‐product of the scale mixture representation, can be used to identify possible outliers. This paper also proposes a uniform scale mixture representation for the GT density, and demonstrates how this density representation alleviates the computational burden of the Gibbs sampler.</jats:p>