DeepAI AI Chat
Log In Sign Up

Objective Bayesian analysis for spatial Student-t regression models

by   Jose A. Ordoñez, et al.
Universidade Federal de Minas Gerais

The choice of the prior distribution is a key aspect of Bayesian analysis. For the spatial regression setting a subjective prior choice for the parameters may not be trivial, from this perspective, using the objective Bayesian analysis framework a reference is introduced for the spatial Student-t regression model with unknown degrees of freedom. The spatial Student-t regression model poses two main challenges when eliciting priors: one for the spatial dependence parameter and the other one for the degrees of freedom. 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 yield to a proper posterior distribution. Simulation studies are used in order to evaluate the performance of the reference prior to a commonly used vague proper prior.


page 1

page 2

page 3

page 4


The effects of degrees of freedom estimation in the Asymmetric GARCH model with Student-t Innovations

This work investigates the effects of using the independent Jeffreys pri...

Theoretical properties of Bayesian Student-t linear regression

Student-t linear regression is a commonly used alternative to the normal...

Objective Bayesian Analysis for the Differential Entropy of the Gamma Distribution

The use of entropy related concepts goes from physics, such as in statis...

Objective Bayesian Analysis of a Cokriging Model for Hierarchical Multifidelity Codes

Autoregressive cokriging models have been widely used to emulate multipl...

Objective priors for divergence-based robust estimation

Objective priors for outlier-robust Bayesian estimation based on diverge...

Propriety of the reference posterior distribution in Gaussian Process regression

In a seminal article, Berger, De Oliveira and Sansó (2001) compare sever...