Titre : "Composite likelihood methods in Markov chain models ."
 
Cristiano Varin
Department of Statistics
University Ca' Foscari - Venice

Abstract:

In many spatial and spatial-temporal models, and more generally in models with complex dependencies, it may be too difficult to carry out full maximum likelihood analysis. Possible remedies includes the use of the composite likelihood. This term indicates a rich class of pseudolikelihoods constructed by composing likelihood-type objects. In this talk, I will discuss the efficiency properties of different type of composite likelihoods for general Markov chain models. The project is motivated by the desire to understand the precise behaviour of composite likelihood methods in a simple but not trivial setting where this can be analysed without the need of simulations. This is a joint project with Prof. Nils Lid Hjort, University of Oslo (Norway).