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
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Journal articles
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https://hal.archives-ouvertes.fr/hal-00383111
Contributor : Jean-François Coeurjolly <>
Submitted on : Tuesday, May 12, 2009 - 10:07:25 AM
Last modification on : Monday, April 9, 2018 - 12:22:32 PM

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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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