Bayesian analysis of correlated binary data when individual information is not available is considered. In particular, a binary outcome is measured on the same subjects of two independent groups at two separate occasions (usually time points). The groups are formulated through a binary exposure...

Competitive balance is an important concept in professional team sports; its measurement is, therefore, a critical issue. One of the most widely used indices, which was introduced for the estimation of seasonal competitive balance is the Concentration Ratio, which is a relatively simple index...

This paper focuses on the Bayesian model average (BMA) using the power-expected-posterior prior in objective Bayesian variable selection under normal linear models. We derive a BMA point estimate of a predicted value, and present computation and evaluation strategies of the prediction accuracy....

In this paper we discuss and present in detail the implementation of Gibbs variable selection as defined by Dellaportas et al. (2000, 2002) using the BUGS software (Spiegelhalter et al. ,'96a,b,c). The specification of the likelihood, prior and pseudo-prior distributions of the parameters as...

We deal with two-way contingency tables having ordered column categories. We use a row effects model wherein each interaction term is assumed to have a multiplicative form involving a row effect parameter and a fixed column score. We propose a methodology to cluster row effects in order to...

We focus on robust Bayesian estimation of the systematic risk of an asset in presence of outlying points. We assume that the returns follow independent normal distributions with a product partition structure on the parameters of interest. A Bayesian decision theoretical approach is used to...

In this paper we present a novel semi-Bayesian model for firm default probability estimation. The methodology is based on multivariate contingent claim analysis and pair copula constructions. For each considered firm, balance sheet data are used to assess the asset value, and to compute its...

In this paper we propose a novel Bayesian methodology for Value-at-Risk computation based on parametric Product Partition Models. Value-at-Risk is a standard tool to measure and control the market risk of an asset or a portfolio, and it is also required for regulatory purposes. Its popularity is...

We deal with contingency table data that are used to examine the relationships between a set of categorical variables or factors. We assume that such relationships can be adequately described by the cond`itional independence structure that is imposed by an undirected graphical model. If the...

In this paper we present a novel Bayesian approach for default probability estimation. The methodology is based on multivariate contingent claim analysis and pair copula theory. Balance sheet data are used to asses the firm value and to compute its default probability. The firm pricing function...