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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Objective Bayesian Analysis of Skew-t Distributions

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Author(s):
Branco, Marcia D'Elia [1] ; Genton, Marc G. [2] ; Liseo, Brunero [3]
Total Authors: 3
Affiliation:
[1] Univ Sao Paulo, Dept Estat, BR-05508 Sao Paulo - Brazil
[2] Texas A&M Univ, Dept Stat, College Stn, TX 77843 - USA
[3] Univ Roma La Sapienza, MEMOTEF, Rome - Italy
Total Affiliations: 3
Document type: Journal article
Source: SCANDINAVIAN JOURNAL OF STATISTICS; v. 40, n. 1, p. 63-85, MAR 2013.
Web of Science Citations: 10
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. (AU)

FAPESP's process: 04/15304-6 - Regression models and applications
Grantee:Heleno Bolfarine
Support Opportunities: Research Projects - Thematic Grants