Parametric estimation of pairwise Gibbs point processes with infinite range interaction - Archive ouverte HAL Access content directly
Journal Articles Bernoulli Year : 2017

Parametric estimation of pairwise Gibbs point processes with infinite range interaction

Abstract

This paper is concerned with statistical inference for infinite range interaction Gibbs point processes and in particular for the large class of Ruelle superstable and lower regular pairwise interaction models. We extend classical statistical methodologies such as the pseudolikelihood and the logistic regression methods, originally defined and studied for finite range models. Then we prove that the associated estimators are strongly consistent and satisfy a central limit theorem, provided the pairwise interaction function tends sufficiently fast to zero. To this end, we introduce a new central limit theorem for almost conditionally centered triangular arrays of random fields.
Fichier principal
Vignette du fichier
cltIR.pdf (687.44 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01092225 , version 1 (08-12-2014)
hal-01092225 , version 2 (17-07-2015)
hal-01092225 , version 3 (01-10-2015)

Identifiers

Cite

Jean-François Coeurjolly, Frédéric Lavancier. Parametric estimation of pairwise Gibbs point processes with infinite range interaction. Bernoulli, 2017, 23 (2), pp.1299-1334. ⟨10.3150/15-BEJ779⟩. ⟨hal-01092225v3⟩
332 View
155 Download

Altmetric

Share

Gmail Facebook X LinkedIn More