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

M Raeisi, F Bonneu, E Gabriel - Spatial Statistics, 2021 - Elsevier
Because most natural phenomena exhibit dependence at multiple scales like locations of
earthquakes or forest fire occurrences, spatio-temporal single-scale point process models …

Stochastic modeling and performance analysis of multi-altitude LEO satellite networks using cox point processes

FS Panjaitan - International Journal of Enterprise Modelling, 2023 - ieia.ristek.or.id
The research focuses on the stochastic modeling and performance analysis of multi-altitude
Low Earth Orbit (LEO) satellite networks using Cox point processes. LEO satellite networks …

Point process models for complex spatio-temporal data

M Raeisi - 2021 - theses.hal.science
The theory of point processes is a branch of spatial statistics. A spatial (and spatiotemporal)
point pattern, as a realization of a point process, is a collection of events for which locations …

A spatio-temporal hybrid Strauss hardcore point process for forest fire occurrences

M Raeisi, F Bonneu, E Gabriel - arXiv preprint arXiv:2308.06726, 2023 - arxiv.org
We propose a new point process model that combines, in the spatio-temporal setting, both
multi-scaling by hybridization and hardcore distances. Our so-called hybrid Strauss …

[PDF][PDF] International Journal of Enterprise Modelling

F Riandari, S Sijabat, FS Panjaitan - academia.edu
Low Earth Orbit (LEO) satellite networks have gained significant attention in recent years
due to their potential to provide global connectivity, high data rates, and low latency (Liu et …

[PDF][PDF] Spatio-temporal hybrid Strauss hardcore point process and application

M Raeisi, F Bonneu, E Gabriel - 2021 - uq.math.cnrs.fr
The theory of point processes is a branch of spatial statistics. A spatial (and spatio-temporal)
point pattern, as a realization of a point process, is a collection of events for which locations …

[引用][C] MODÈLES DE PROCESSUS PONCTUELS POUR DES DONNÉES SPATIO-TEMPORELLES COMPLEXES