Open Access
March 2021 Objective Bayesian Analysis for the Student-t Linear Regression
Daojiang He, Dongchu Sun, Lei He
Author Affiliations +
Bayesian Anal. 16(1): 129-145 (March 2021). DOI: 10.1214/20-BA1198


In this paper, objective Bayesian analysis for the Student-t linear regression model with unknown degrees of freedom is studied. The reference priors under all the possible group orderings for the parameters in the model are derived. The posterior propriety under each reference prior is validated by considering a larger class of priors. Simulation studies are carried out to investigate the frequentist properties of Bayesian estimators based on the reference priors. Finally, the Bayesian approach is applied to two real data sets.


The authors are very grateful to the Editor-in-Chief, the Editor, the Associate Editor and the two anonymous Reviewers for their valuable comments and suggestions on earlier versions of this paper.


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Daojiang He. Dongchu Sun. Lei He. "Objective Bayesian Analysis for the Student-t Linear Regression." Bayesian Anal. 16 (1) 129 - 145, March 2021.


Published: March 2021
First available in Project Euclid: 10 March 2020

MathSciNet: MR4194276
Digital Object Identifier: 10.1214/20-BA1198

Primary: 62F15
Secondary: 62J05

Keywords: independent Jeffreys prior , reference prior , Scale mixture of normals

Vol.16 • No. 1 • March 2021
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