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A new class of multivariate skew distributions with applications to Bayesian regression models

Record type: Article

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.

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Citation

Sahu, S.K., Dey, D.K. and Branco, M.D. (2003) A new class of multivariate skew distributions with applications to Bayesian regression models Canadian Journal of Statistics, 31, (2), pp. 129-150. (doi:10.2307/3316064).

More information

Published date: 2003
Keywords: Bayesian Inference, elliptical distributions, heavy tailed error distribution, gibbs sampler, markov chain Monte Carlo, Multivariate skewness
Organisations: Statistics

Identifiers

Local EPrints ID: 30176
URI: http://eprints.soton.ac.uk/id/eprint/30176
ISSN: 0319-5724
PURE UUID: 8315475c-d47e-48e6-a8e1-42534b33cd11
ORCID for S.K. Sahu: ORCID iD orcid.org/0000-0003-2315-3598

Catalogue record

Date deposited: 11 May 2006
Last modified: 17 Jul 2017 15:55

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