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

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dc.creatorBilliot, Jean-Michel
dc.creatorCoeurjolly, Jean-François
dc.creatorDrouilhet, Rémy
dc.date2008-04-23
dc.date.accessioned2026-07-07T12:18:27Z
dc.date.available2026-07-07T12:18:27Z
dc.descriptionThis paper is devoted to the estimation of a vector $\bm θ$ 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.
dc.descriptionPublished in at http://dx.doi.org/10.1214/07-EJS160 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0804.3715
dc.identifierhttp://arxiv.org/abs/0804.3715
dc.identifierElectronic Journal of Statistics 2008, Vol. 2, 234-264
dc.identifierdoi:10.1214/07-EJS160
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/212416
dc.subjectStatistics Theory
dc.subject60G55 (Primary) 60J25 (Secondary)
dc.titleMaximum pseudolikelihood estimator for exponential family models of marked Gibbs point processes
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