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 …

This review paper surveys recent development in software implementations for extreme
value analyses since the publication of Stephenson and Gilleland (Extremes 8: 87–109,) …

Max-stable processes are natural models for spatial extremes because they provide suitable
asymptotic approximations to the distribution of maxima of random fields. In the recent past …

For d≥ 2 risk variables, three methods have been proposed to estimate the multivariate tail
quantities, including multivariate tail probabilities, tail dependence functions and tail quantile …

In many practical applications, evaluating the joint impact of combinations of environmental
variables is important for risk management and structural design analysis. When such …

To explicitly account for asymptotic dependence between rainfall intensity maxima of
different accumulation duration, a recent development for estimating Intensity-Duration …

With their severe environmental and socioeconomic impact, drought events belong to the
most far-reaching natural disasters. Effects are tremendous in rain-fed agricultural areas as …

A bivariate extreme-value copula is characterized by its Pickands dependence function, ie, a
convex function defined on the unit interval satisfying boundary conditions. This paper …

Various nonparametric and parametric estimators of extremal dependence have been
proposed in the literature. Nonparametric methods commonly suffer from the curse of …

The dependence structure of max-stable random vectors can be characterized by their
Pickands dependence function. In many applications, the extremal dependence measure …