592 citations · 801 across the 15 of their papers we have counts for
17 papers
Spatio-temporal point process intensity estimation using zero-deflated subsampling applied to a lightning strikes dataset in France
Jean-François Coeurjolly, Thibault Espinasse, Anne-Laure Fougères +1
Cloud-to-ground lightning strikes observed in a specific geographical domain over time can be naturally modeled by a spatio-temporal point process. Our focus lies in the parametric…
Spatial modeling of extremes and an angular component
Gaspard Tamagny, Mathieu Ribatet
Many environmental processes such as rainfall, wind or snowfall are inherently spatial and the modelling of extremes has to take into account that feature. In addition, environment…
Full likelihood inference for max-stable data
Raphaël Huser, Clément Dombry, Mathieu Ribatet +1
We show how to perform full likelihood inference for max-stable multivariate distributions or processes based on a stochastic Expectation-Maximisation algorithm, which combines sta…
ABC random forests for Bayesian parameter inference
Louis Raynal, Jean-Michel Marin, Pierre Pudlo +3
This preprint has been reviewed and recommended by Peer Community In Evolutionary Biology (http://dx.doi.org/10.24072/pci.evolbiol.100036). Approximate Bayesian computation (ABC) h…
Probabilities of concurrent extremes
Clément Dombry, Mathieu Ribatet, Stilian Stoev
The statistical modelling of spatial extremes has recently made major advances. Much of its focus so far has been on the modelling of the magnitudes of extreme events but little at…
Conditional simulation of max-stable processes
Clément Dombry, Frédéric Éyi-Minko, Mathieu Ribatet
Since many environmental processes such as heat waves or precipitation are spatial in extent, it is likely that a single extreme event affects several locations and the areal model…