activity
20172026
most citedHierarchical space-time modeling of exceedances with an application to rainfall data

3 citations · 3 across the 8 of their papers we have counts for

collaborators

8 papers

stat.AP2026

Spatio-temporal modeling of urban extreme rainfall events at high resolution

Chloé Serre-Combe, Nicolas Meyer, Thomas Opitz +1

Modeling precipitation and its accumulation over time and space is essential for flood risk assessment. In this paper, we analyze rainfall data collected over several years through…

math.ST2024

Tree Pólya Splitting distributions for multivariate count data

Samuel Valiquette, Jean Peyhardi, Éric Marchand +2

In this article, we develop a new class of multivariate distributions adapted for count data, called Tree Pólya Splitting. This class results from the combination of a univariate d…

stat.AP2023

Identifying regions of concomitant compound precipitation and wind speed extremes over Europe

Alexis Boulin, Elena Di Bernardino, Thomas Laloë +1

The task of simplifying the complex spatio-temporal variables associated with climate modeling is of utmost importance and comes with significant challenges. In this research, our…

math.ST2023

Asymptotic tail properties of Poisson mixture distributions

Samuel Valiquette, Gwladys Toulemonde, Jean Peyhardi +2

Count data are omnipresent in many applied fields, often with overdispersion. With mixtures of Poisson distributions representing an elegant and appealing modelling strategy, we fo…

math.ST2023

High-dimensional variable clustering based on maxima of a weakly dependent random process

Alexis Boulin, Elena Di Bernardino, Thomas Laloë +1

We propose a new class of models for variable clustering called Asymptotic Independent block (AI-block) models, which defines population-level clusters based on the independence of…

math.ST2022

Choice of mixture Poisson models based on Extreme value theory

Samuel Valiquette, Frédéric Mortier, Jean Peyhardi +1

Count data are omnipresent in many applied fields, often with overdispersion due to an excess of zeroes or extreme values. With mixtures of Poisson distributions representing an el…

math.ST2021

Non-parametric estimator of a multivariate madogram for missing-data and extreme value framework

Alexis Boulin, Elena Di Bernardino, Thomas Laloë +1

The modeling of dependence between maxima is an important subject in several applications in risk analysis. To this aim, the extreme value copula function, characterised via the ma…

stat.ME2017★ 3 cited

Hierarchical space-time modeling of exceedances with an application to rainfall data

Jean-Noel Bacro, Carlo Gaetan, Thomas Opitz +1

The statistical modeling of space-time extremes in environmental applications is key to understanding complex dependence structures in original event data and to generating realist…