Maximum pseudo-likelihood estimator for nearest-neighbours Gibbs point processes
Statistics Theory
2016-08-16 v1 Statistics Theory
Abstract
This paper is devoted to the estimation of a vector parametrizing an energy function associated to some "Nearest-Neighbours" Gibbs point process, via the pseudo-likelihood method. We present some convergence results concerning this estimator, that is strong consistency and asymptotic normality, when only a single realization is observed. Sufficient conditions are expressed in terms of the local energy function and are verified on some examples.
Cite
@article{arxiv.math/0601065,
title = {Maximum pseudo-likelihood estimator for nearest-neighbours Gibbs point processes},
author = {Jean-Michel Billiot and Jean-François Coeurjolly and Rémy Drouilhet},
journal= {arXiv preprint arXiv:math/0601065},
year = {2016}
}
Comments
29 pages - 2 figures