Nonparametric tests for Cox processes

Abstract : In a functional setting, we elaborate and study two test statistics to highlight the Poisson nature of a Cox process when n copies of the process are available. Our approach involves a comparison of the empirical mean and the empirical variance of the functional data and can be seen as an extended version of a classical overdispersion test for count data. The limiting distributions of our statistics are derived using a functional central limit theorem for c`adì ag martingales. Our procedures are easily implementable and do not require any knowledge on the covariate. We address a theoretical comparison of the asymptotic power of our tests under some local alternatives. A numerical study reveals the good performances of the method. We also present two applications of our tests to real data sets.
Type de document :
Article dans une revue
Journal of Statistical Planning and Inference, Elsevier, 2017, 184, pp.48-61. <10.1016/j.jspi.2016.12.001>
Liste complète des métadonnées


https://hal.archives-ouvertes.fr/hal-01430572
Contributeur : Benoît Cadre <>
Soumis le : mardi 10 janvier 2017 - 09:44:17
Dernière modification le : jeudi 15 juin 2017 - 09:08:57
Document(s) archivé(s) le : mardi 11 avril 2017 - 13:34:15

Fichier

COX.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Citation

Benoît Cadre, Gaspar Massiot, Lionel Truquet. Nonparametric tests for Cox processes. Journal of Statistical Planning and Inference, Elsevier, 2017, 184, pp.48-61. <10.1016/j.jspi.2016.12.001>. <hal-01430572>

Partager

Métriques

Consultations de
la notice

191

Téléchargements du document

101