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Takacs Fiksel method for stationary marked Gibbs point processes
Jean-François Coeurjolly 1, 2, David Dereudre 3, Rémy Drouilhet 2, Frédéric Lavancier 4
(2010-07-20)

This paper studies a method to estimate the parameters governing the distribution of a stationary marked Gibbs point process. This method, known as the Takacs-Fiksel method, is based on the estimation of the left and right hand sides of the Georgii-Nguyen-Zessin formula and leads to a family of estimators due to the possible choices of test functions. We propose several examples illustrating the interest and flexibility of this procedure. We also provide sufficient conditions based on the model and the test functions to derive asymptotic properties (consistency and asymptotic normality) of the resulting estimator. The different assumptions are discussed for exponential family models and for a large class of test functions.
1:  Grenoble Images Parole Signal Automatique (GIPSA-lab)
CNRS : UMR5216 – Université Joseph Fourier - Grenoble I – Université Pierre-Mendès-France - Grenoble II – Université Stendhal - Grenoble III – Institut Polytechnique de Grenoble - Grenoble Institute of Technology
2:  Laboratoire Jean Kuntzmann (LJK)
CNRS : UMR5224 – Université Joseph Fourier - Grenoble I – Université Pierre-Mendès-France - Grenoble II – Institut Polytechnique de Grenoble - Grenoble Institute of Technology
3:  Laboratoire de Mathématiques et leurs Applications de Valenciennes, EA 45 (LAMAV)
Université de Valenciennes et du Hainaut-Cambresis – CNRS : FRE2956
4:  Laboratoire de Mathématiques Jean Leray (LMJL)
CNRS : UMR6629 – Université de Nantes – École Centrale de Nantes
Mathematics/Statistics

Statistics/Statistics Theory
stationary marked Gibbs point processes – parametric estimation – Takacs-Fiksel method – asymptotic properties – ergodic theorem – central limit theorem
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