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

Rapid growth of the use of wind energy calls for a more careful representation of wind speed
probability distribution, both for identification and estimation purposes. In particular, a key …

Currently available models for spatial extremes suffer either from inflexibility in the
dependence structures that they can capture, lack of scalability to high dimensions, or in …

Mitigating the risk arising from extreme events is a fundamental goal with many applications,
such as the modelling of natural disasters, financial crashes, epidemics, and many others …

Modelling extremes of spatial aggregates of precipitation using conditional methods Page 1
The Annals of Applied Statistics 2022, Vol. 16, No. 4, 2693–2713 https://doi.org/10.1214/22-AOAS1609 …

Extreme-value theory has been explored in considerable detail for univariate and low-
dimensional observations, but the field is still in an early stage regarding high-dimensional …

In this paper, we presented a financial analysis of the values of financial losses for real data
in light of a set of indicators for measuring financial risks. The value-at-risk (VAR), tail mean …

Recursive max-linear vectors provide models for the causal dependence between large
values of observed random variables as they are supported on directed acyclic graphs …

Physical considerations and previous studies suggest that extremal dependence between
ocean storm severity at two locations exhibits near asymptotic dependence at short inter …

Although most models for rainfall extremes focus on pointwise values, it is aggregated
precipitation over areas up to river catchment scale that is of the most interest. To capture the …