A spatio-temporal multi-scale model for Geyer saturation point process: application to forest fire occurrences - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Spatial Statistics Année : 2021

A spatio-temporal multi-scale model for Geyer saturation point process: application to forest fire occurrences

Résumé

Because most natural phenomena exhibit dependence at multiple scales like locations of earthquakes or forest fire occurrences, spatio-temporal single-scale point process models are unrealistic in many applications. This motivates us to construct generalizations of classical Gibbs models. In this paper, we extend the Geyer saturation point process model to the spatio-temporal multi-scale framework. The simulation process is carried out through a birth–death Metropolis–Hastings algorithm. In a simulation study, we compare two common methods for statistical inference in Gibbs models: the pseudo-likelihood and logistic likelihood approaches that we tailor to this model. Finally, we illustrate this new model on forest fire occurrences modeling in Southern France.
Fichier principal
Vignette du fichier
S2211675321000026.pdf (802.84 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-02917339 , version 1 (13-02-2023)

Licence

Copyright (Tous droits réservés)

Identifiants

Citer

Morteza Raeisi, Florent Bonneu, Edith Gabriel. A spatio-temporal multi-scale model for Geyer saturation point process: application to forest fire occurrences. Spatial Statistics, 2021, 41, pp.100492. ⟨10.1016/j.spasta.2021.100492⟩. ⟨hal-02917339⟩
69 Consultations
6 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More