In recent years the Dirichlet process prior has experienced a great success in the context of Bayesian mixture modelling. The idea of overcoming discreteness of its realizations by exploiting it in hierarchical models, combined with the development of suitable sampling techniques, represent one...

Following Lence and Hayes (1994a), we study the problem faced by an Iowa farmer who wishes to hedge a soybean harvest using Chicago futures contracts. A time-series model for spot and futures prices is postulated, and numerical Bayesian procedures are used to calculate predictive densities and...

En este trabajo se propone un modelo jerárquico Gamma para el estudio bayesiano de tiempos de desempleo con covariables utilizando técnicas de análisis de supervivencia. Se trata de un modelo de efectos aleatorios o modelo de poblaciones debido a su estructura jerárquica, que permite la...

The cost functions used to form forecasts in practice may be quite different than the squared costs that is often assumed in forecast theory. The impact on evaluation procedures is determined and simple properties for the derivate of the cost function of the errors are found to provide simple...

Exponential smoothing methods do not involve a formal procedure for identifying the underlying data generating process. The issue is then whether prediction intervals should be estimated by a theoretical approach, with the assumption that the method is optimal in some sense, or by an empirical...

A Polya tree is characterised by a special class of predictive probabilities.