A new class of multivariate skew distributions with applications to Bayesian regression models
Sahu, S.K., Dey, D.K. and Branco, M.D. (2003) A new class of multivariate skew distributions with applications to Bayesian regression models. The Canadian Journal of Statistics, 31, (2), 129-150. (doi:10.2307/3316064).
This article develops a new class of distributions by introducing skewness in the multivariate elliptically symmetric distributions. The class is obtained by using transformation and conditioning. The class contains many standard families including the multivariate skew normal and t distributions. Analytical forms of the densities are obtained and distributional properties are studied.
These developments are followed by practical examples in Bayesian regression models. Results on the existence of the posterior distributions and moments under improper priors for the regression
coefficients are obtained. The methods are illustrated using practical examples.
|Digital Object Identifier (DOI):||doi:10.2307/3316064|
|Keywords:||Bayesian Inference, elliptical distributions, heavy tailed error distribution, gibbs sampler, markov chain Monte Carlo, Multivariate skewness|
|Subjects:||Q Science > QA Mathematics
H Social Sciences > HA Statistics
|Divisions:||University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute
University Structure - Pre August 2011 > School of Mathematics > Statistics
|Date Deposited:||11 May 2006|
|Last Modified:||06 Aug 2015 02:30|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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