TOULEMONDE , Gwladys

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 primary objective is to tailor clustering techniques to handle compound extreme events within gridded climate data across Europe. Specifically, we intend to identify...

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 madogram, can be used as a margin-free description of the dependence structure. From a practical point of view, the family of extreme value distributions is very rich...

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 the maxima of a multivariate stationary mixing random process among clusters. This class of models is identifiable, meaning that there exists a maximal element with...

International audience

International audience

International audience

International audience

Modéliser la dépendance entre maxima est un sujet d'intérêt dans les domaines d'application d'analyse du risque. Dans cet objectif, la copule de valeurs extrêmes, caractérisée par le madogramme, peut être utilisée comme une description de la structure de dépendance. Concrètement, la famille des distributions à valeurs extrêmes est très riche...

The dependence structure between extreme observations can be complex. For that purpose, we see clustering as a tool for learning the complexextremal dependence structure. We introduce the Asymptotic Independent block (AI-block) model, a model-based clustering where population-level clusters are clearly defined using independence of clusters'...

International audience