Objective Bayesian analysis for geostatistical Student-t processes

ABSTRACT

The choice of the prior distribution is a key aspect of Bayesian analysis. The spatial Student-t regression model poses some challenges when eliciting priors. It is well known that the propriety of the posterior distribution over objective priors is not always guaranteed, whereas the use of proper prior distributions may dominate and bias the posterior analysis. In this paper, we show the conditions under which our proposed reference prior and the two introduced Jeffreys priors yield to a proper posterior distribution. Simulation studies and a real data application are used in order to evaluate the performance of the reference prior.

KEYWORDS:

• Geostatistics
• multivariate Student-t distribution
• objective prior
• proper prior

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/14498596.2023.2170930

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

The research of Jose A. Ordoñez was financed in part by CAPES - Brazil (Finance Code 001). Marcos O. Prates would like to acknowledge CNPq - Brazil and FAPEMIG - Brazil for partial financial support.