Maximum pseudolikelihood estimator for exponential family models of marked Gibbs point processes
Statistics Theory
2008-12-18 v1 Statistics Theory
Abstract
This paper is devoted to the estimation of a vector 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.
Cite
@article{arxiv.0804.3715,
title = {Maximum pseudolikelihood estimator for exponential family models of marked Gibbs point processes},
author = {Jean-Michel Billiot and Jean-François Coeurjolly and Rémy Drouilhet},
journal= {arXiv preprint arXiv:0804.3715},
year = {2008}
}
Comments
Published 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)