We develop a Bayesian analysis based on two different Jeffreys priors for the Student-t regression model with unknown degrees of freedom. It is typically difficult to estimate the number of degrees of freedom: improper prior distributions may lead to improper posterior distributions, whereas proper prior distributions may dominate the analysis. We show that Bayesian analysis with either of the two considered Jeffreys priors provides a proper posterior distribution. Finally, we show that Bayesian estimators based on Jeffreys analysis compare favourably to other Bayesian estimators based on priors previously proposed in the literature
In this paper, we construct an objective prior for the degrees of freedom of a t distribution, when ...
It is typically difficult to estimate the number of degrees of freedom due to the leptokurtic nature...
Insurance risks data typically exhibit skewed behaviour. In this paper, we propose a Bayesian approa...
We develop a Bayesian analysis based on two different Jeffreys priors for the Student-t regres-sion ...
The choice of the prior distribution is a key aspect of Bayesian analysis. The spatial Student-t reg...
We study the Jeffreys prior and its properties for the shape parameter of univariate skew-t distribu...
Neste trabalho, apresentamos uma extensão da análise bayesiana objetiva feita em Fonseca et al. (200...
Neste trabalho, apresentamos uma extensão da análise bayesiana objetiva feita em Fonseca et al. (200...
This article takes up methods for Bayesian inference in a linear model in which the disturbances are...
In this paper, we construct an objective prior for the degrees of freedom of a t distribution, when ...
In this paper, we construct an objective prior for the degrees of freedom of a t distribution, when ...
In this paper, we construct an objective prior for the degrees of freedom of a t distribution, when ...
In this paper, we construct an objective prior for the degrees of freedom of a t distribution, when ...
In this paper, we construct an objective prior for the degrees of freedom of a t distribution, when ...
We consider likelihood-based inference from multivariate regression models with independent Student-...
In this paper, we construct an objective prior for the degrees of freedom of a t distribution, when ...
It is typically difficult to estimate the number of degrees of freedom due to the leptokurtic nature...
Insurance risks data typically exhibit skewed behaviour. In this paper, we propose a Bayesian approa...
We develop a Bayesian analysis based on two different Jeffreys priors for the Student-t regres-sion ...
The choice of the prior distribution is a key aspect of Bayesian analysis. The spatial Student-t reg...
We study the Jeffreys prior and its properties for the shape parameter of univariate skew-t distribu...
Neste trabalho, apresentamos uma extensão da análise bayesiana objetiva feita em Fonseca et al. (200...
Neste trabalho, apresentamos uma extensão da análise bayesiana objetiva feita em Fonseca et al. (200...
This article takes up methods for Bayesian inference in a linear model in which the disturbances are...
In this paper, we construct an objective prior for the degrees of freedom of a t distribution, when ...
In this paper, we construct an objective prior for the degrees of freedom of a t distribution, when ...
In this paper, we construct an objective prior for the degrees of freedom of a t distribution, when ...
In this paper, we construct an objective prior for the degrees of freedom of a t distribution, when ...
In this paper, we construct an objective prior for the degrees of freedom of a t distribution, when ...
We consider likelihood-based inference from multivariate regression models with independent Student-...
In this paper, we construct an objective prior for the degrees of freedom of a t distribution, when ...
It is typically difficult to estimate the number of degrees of freedom due to the leptokurtic nature...
Insurance risks data typically exhibit skewed behaviour. In this paper, we propose a Bayesian approa...