Maximum pseudolikelihood estimator for exponential family models of marked {Gibbs} point processes

Jean-François Coeurjolly 1 Jean-Michel Billiot 1 Rémy Drouilhet 1
1 SAGAG - Statistique Appliquée et de Géométrie Aléatoire de Grenoble
LJK - Laboratoire Jean Kuntzmann
Abstract : This paper is devoted to the estimation of a vector θ parametrizing an energy function of a Gibbs point process, via the maximum pseudolikelihood method. Strong consistency and asymptotic normality results of this estimator depending on a single realization are presented. In the framework of exponential family models, sufficient conditions are expressed in terms of the local energy function and are verified on a wide variety of examples.
Keywords : stationary marked Gibbs point processes pseudolikelihood method minimum contrast estimators
Type de document :
Article dans une revue
Electronic journal of statistics , Shaker Heights, OH : Institute of Mathematical Statistics, 2008, 2, pp.243-264. 〈10.1214/07-EJS160〉
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https://hal.archives-ouvertes.fr/hal-00383111
Contributeur : Jean-François Coeurjolly <>
Soumis le : mardi 12 mai 2009 - 10:07:25
Dernière modification le : lundi 9 avril 2018 - 12:22:32

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Jean-François Coeurjolly, Jean-Michel Billiot, Rémy Drouilhet. Maximum pseudolikelihood estimator for exponential family models of marked {Gibbs} point processes. Electronic journal of statistics , Shaker Heights, OH : Institute of Mathematical Statistics, 2008, 2, pp.243-264. 〈10.1214/07-EJS160〉. 〈hal-00383111〉

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