Objective Bayesian Analysis of Skew- t Distributions

MARCIA D'ELIA BRANCO, Marc G. Genton, BRUNERO LISEO

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

We study the Jeffreys prior and its properties for the shape parameter of univariate skew-t distributions with linear and nonlinear Student's t skewing functions. In both cases, we show that the resulting priors for the shape parameter are symmetric around zero and proper. Moreover, we propose a Student's t approximation of the Jeffreys prior that makes an objective Bayesian analysis easy to perform. We carry out a Monte Carlo simulation study that demonstrates an overall better behaviour of the maximum a posteriori estimator compared with the maximum likelihood estimator. We also compare the frequentist coverage of the credible intervals based on the Jeffreys prior and its approximation and show that they are similar. We further discuss location-scale models under scale mixtures of skew-normal distributions and show some conditions for the existence of the posterior distribution and its moments. Finally, we present three numerical examples to illustrate the implications of our results on inference for skew-t distributions. © 2012 Board of the Foundation of the Scandinavian Journal of Statistics.
Original languageEnglish (US)
Pages (from-to)63-85
Number of pages23
JournalScandinavian Journal of Statistics
Volume40
Issue number1
DOIs
StatePublished - Feb 27 2012
Externally publishedYes

Fingerprint

Dive into the research topics of 'Objective Bayesian Analysis of Skew- t Distributions'. Together they form a unique fingerprint.

Cite this