Conditional independence, graphical models and sparsity are key notions for parsimonious
statistical models and for understanding the structural relationships in the data. The theory of …

The health consequences of climate variability and change are diverse, potentially affecting
the burden of a wide range of health outcomes, including illnesses and deaths related to …

A Horse Race between the Block Maxima Method and the Peak-over-Threshold Approach
Page 1 Statistical Science 2021, Vol. 36, No. 3, 360–378 https://doi.org/10.1214/20-STS795 © …

Being the max-analogue of α-stable stochastic processes, max-stable processes form one of
the fundamental classes of stochastic processes. With the arrival of sufficient computational …

To better manage the risks of destructive natural disasters, impact models can be fed with
simulations of extreme scenarios to study the sensitivity to temporal and spatial variability …

We consider the random field M (t)= sup _ n\geq1 {-\log A_ n+ X_ n (t)\},\qquad t ∈ T, for a
set T⊂R^m, where (X_n) is an iid sequence of centered Gaussian random fields on T and …

We consider the random field M (t)=\sup_ {n\geq 1}\big\{-\log A_ {n}+ X_ {n}(t)\big\}\,,\qquad
t\in T\, for a set $ T\subset\mathbb {R}^{m} $, where $(X_ {n}) $ is an iid sequence of …

Max-stable processes are a popular tool for the study of environmental extremes, and the
extremal skew-t process is a general model that allows for a flexible extremal dependence …

This research includes extreme spatial values. Application of the method with the Max-
Stable (MSP) process. The approach will be used for the analysis of extreme rainfall in …

We review some recent development in the theory of spatial extremes related to Pareto
Processes and modeling of threshold exceedances. We provide theoretical background …