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



Electronic Journal of Statistics

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

Jean-Michel Billiot, Jean-François Coeurjolly and Rémy Drouilhet

Source: Electron. J. Statist. Volume 2 (2008), 234-264.

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.

Primary Subjects: 60G55
Secondary Subjects: 60J25
Keywords: stationary marked Gibbs point processes; pseudolikelihood method; minimum contrast estimators

Full-text: Access granted (open access)

Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.ejs/1208958317
Digital Object Identifier: doi:10.1214/07-EJS160

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