Title :

Consistency of likelihood estimation for Gibbs point processes

Author(s) :

Dereudre, David [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Lavancier, Frédéric [Auteur]
Laboratoire de Mathématiques Jean Leray [LMJL]
Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes [SERPICO]

Journal title :

Annals of Statistics

Publisher :

Institute of Mathematical Statistics

Publication date :

2016

ISSN :

0090-5364

English keyword(s) :

Parametric estimation
Area-interaction model
Lennard-Jones model
Strauss model
Variational principle

HAL domain(s) :

Statistiques [stat]/Théorie [stat.TH]

English abstract : [en]

Strong consistency of the maximum likelihood estimator (MLE) for parametric Gibbs point process models is established. The setting is very general. It includes pairwise pair potentials, finite and infinite multibody ...
Show more >Strong consistency of the maximum likelihood estimator (MLE) for parametric Gibbs point process models is established. The setting is very general. It includes pairwise pair potentials, finite and infinite multibody interactions and geometrical interactions, where the range can be finite or infinite. The Gibbs interaction may depend linearly or non-linearly on the parameters, a particular case being hardcore parameters and interaction range parameters. As important examples, we deduce the consistency of the MLE for all parameters of the Strauss model, the hardcore Strauss model, the Lennard-Jones model and the area-interaction model.Show less >

Language :

Anglais

Popular science :

Non

ANR Project :

Centre de Mathématiques Henri Lebesgue : fondements, interactions, applications et Formation

Collections :

• Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL