Hidden Markov Models can be considered an extension of mixture models, allowing fordependent observations. In a hierarchical Bayesian framework, we show how ReversibleJump Markov Chain Monte Carlo techniques can be used to estimate the parameters of amodel, as well as the number of regimes. We...

This paper investigates transport providers’ preferences for alternative loading bays and pricing policies. It estimates the importance of loading bays, the probability of finding them free and offers strategically relevant information to policy makers. The results underline the relevance of...

This paper systematically compares methods to build confidence intervals for willingness to pay measures in a discrete choice context. It contributes to the literature by including methods developed in other research fields. Monte Carlo simulations are used to assess the performance of all the...

This paper shows that, when modelling freight demand, taking into consideration the presence of attribute cutoffs is important and has relevant repercussions on the estimates of service attributes coefficients. In this paper we focus on mode choice models for freight transport demand in the...

We propose a Bayesian nonparametric model to estimate rating migration matrices and default probabilities using the reinforced urn processes (RUP) introduced in Muliere et al. (2000). The estimated default probability becomes our prior information in a parametric model for the prediction of the...

We propose a test based on Bonferroni's measure of skewness. The test detects the asymmetry of a distribution function about an unknown median. We study the asymptotic distribution of the given test statistic and provide a consistent estimate of its variance. The asymptotic relative efficiency...

The class of finite state space Markov chains, stationary with respect to a common pre-specified distribution, is considered. An easy-to-check partial ordering is defined on this class. The ordering provides a sufficient condition for the dominating Markov chain to be more efficient. Efficiency...