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).


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Original Publication URL: http://dx.doi.org/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.

Item Type: Article
Digital Object Identifier (DOI): doi:10.2307/3316064
ISSNs: 0319-5724 (print)
Related URLs:
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
ePrint ID: 30176
Accepted Date and Publication Date:
Date Deposited: 11 May 2006
Last Modified: 31 Mar 2016 11:56
URI: http://eprints.soton.ac.uk/id/eprint/30176

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