Robust Bayesian analysis is the study of the sensitivity of Bayesian answers to uncertain
inputs. This paper seeks to provide an overview of the subject, one that is accessible to …

Almost all the results available in the literature on multivariate t-distributions published in the
last 50 years are now collected together in this comprehensive reference. Because these …

Abstract: The authors develop a new class of distributions by introducing skewness in
multivariate elliptically symmetric distributions. The class, which is obtained by using …

A Bayesian approach to estimation, prediction, and model comparison in composed error
production models is presented. A broad range of distributions on the inefficiency term …

International migration is becoming an increasingly important element of contemporary
demographic dynamics and yet, due to its high volatility, it remains the most unpredictable …

A new class of continuous multivariate distributions on×∈ ℜ n is proposed. We define these
so-called υ-spherical distributions through properties of the density function in a location …

This paper takes up Bayesian inference in a general trend stationary model for
macroeconomic time series with independent Student-t disturbances. The model is linear in …

With the introductory paragraph, we explain the fundamental concepts and basic notions of
this section. For you, the analyst, who has the difficult task to deal with measurements …

This paper considers a Bayesian analysis of the linear regression model under independent
sampling from general scale mixtures of normals. Using a common reference prior, we …

This paper provides a Bayesian analysis of Autoregressive Fractionally Integrated Moving
Average (ARFIMA) models. We discuss in detail inference on impulse responsens, and …