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This work presents a construction of stationary Markov models with negative-binomial marginal distributions. A simple closed form expression for the corresponding transition probabilities is given, linking the proposal to well-known classes of birth and death processes and thus revealing interesting characterizations. The advantage of having such closed form expressions is tested on simulated and real data. [ABSTRACT FROM AUTHOR]

Abstract A loss-based approach to change point analysis is proposed. In particular, the problem is looked from two perspectives. The first focuses on the definition of a prior when the number of change points is known a priori. The second contribution aims to estimate the number of change points by using a loss-based approach recently introduced in the literature. The latter considers change point estimation as a model selection exercise. The performance of the proposed approach is shown on simulated data and real data sets. [ABSTRACT FROM AUTHOR]

Compound random measures (CoRM’s) are a flexible and tractable framework for vectors of completely random measure. In this paper, we provide conditions to guarantee the existence of a CoRM. Furthermore, we prove some interesting properties of CoRM’s when exponential scores and regularly varying Lévy intensities are considered. [ABSTRACT FROM AUTHOR]

Abstract: Move-to-front rule is a heuristic updating a list of items according to requests. Items are required with unknown probabilities (or popularities). The induced Markov chain is known to be ergodic. A main problem is the study of the distribution of the search cost defined as the position of the required item. Here we first establish the link between two recent papers of Barrera and Paroissin and Lijoi and Pruenster that both extend the results proved by Kingman on the expected stationary search cost. By combining the results contained in these papers, we obtain the limiting behavior for any moments of the stationary search cost as tends to infinity. [Copyright &y& Elsevier]

Abstract: In this paper the notion of variance bounding introduced by is extended to continuous time Markov Chains. Moreover, it is proven that, as in the discrete time case, the notion of variance bounding for reversible Markov Chains is equivalent to the existence of a central limit theorem. A connection with the continuous time Peskun ordering, introduced by , concludes the paper. [ABSTRACT FROM AUTHOR]

In this paper the theory of species sampling sequences is linked to the theory of conditionally identically distributed sequences in order to enlarge the set of species sampling sequences which are mathematically tractable. The conditional identity in distribution (see Berti, Pratelli and Rigo (2004)) is a new type of dependence for random variables, which generalizes the well-known notion of exchangeability. In this paper a class of random sequences, called generalized species sampling sequences, is defined and a condition to have conditional identity in distribution is given. Moreover, two types of generalized species sampling sequence that are conditionally identically distributed are introduced and studied: the generalized Poisson-Dirichlet sequenceand the generalized Ottawa sequence. Some examples are discussed.