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Statistica Sinica 21 (2011), 129-148



Luigi Pace, Alessandra Salvan and Nicola Sartori

University of Udine, University of Padova and University of Padova

Abstract: Composite likelihood may be useful for approximating likelihood based inference when the full likelihood is too complex to deal with. Stemming from a misspecified model, inference based on composite likelihood requires suitable corrections. Here we focus on the composite likelihood ratio statistic for a multidimensional parameter of interest, and we propose a parameterization invariant adjustment that allows reference to the usual asymptotic chi-square distribution. Two examples dealing with pairwise likelihood are analysed through simulation.

Key words and phrases: Equicorrelated multivariate normal distribution, first-order autoregression, Godambe information, pairwise likelihood, pseudolikelihood.

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