Advances in statistical modeling of spatial extremes

R Huser, JL Wadsworth - Wiley Interdisciplinary Reviews …, 2022 - Wiley Online Library
The classical modeling of spatial extremes relies on asymptotic models (ie, max‐stable or r‐
Pareto processes) for block maxima or peaks over high thresholds, respectively. However, at …

Graphical models for extremes

S Engelke, AS Hitz - Journal of the Royal Statistical Society …, 2020 - academic.oup.com
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 …

Modeling spatial processes with unknown extremal dependence class

R Huser, JL Wadsworth - Journal of the American statistical …, 2019 - Taylor & Francis
Many environmental processes exhibit weakening spatial dependence as events become
more extreme. Well-known limiting models, such as max-stable or generalized Pareto …

Assessment of the joint impact of extreme rainfall and storm surge on the risk of flooding in a coastal area

B Zellou, H Rahali - Journal of Hydrology, 2019 - Elsevier
In coastal areas, flood events can result from the interaction of several factors such as
rainfall, river flow and the classical tidal asymmetry to mention but a few. Therefore, flood risk …

INLA goes extreme: Bayesian tail regression for the estimation of high spatio-temporal quantiles

T Opitz, R Huser, H Bakka, H Rue - Extremes, 2018 - Springer
This work is motivated by the challenge organized for the 10th International Conference on
Extreme-Value Analysis (EVA2017) to predict daily precipitation quantiles at the 99.8 …

Spatial extremes

AC Davison, R Huser, E Thibaud - Handbook of environmental …, 2019 - taylorfrancis.com
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 …

[HTML][HTML] Higher-dimensional spatial extremes via single-site conditioning

JL Wadsworth, JA Tawn - Spatial Statistics, 2022 - Elsevier
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 …

An evaluation of the consistency of extremes in gridded precipitation data sets

B Timmermans, M Wehner, D Cooley, T O'Brien… - Climate dynamics, 2019 - Springer
Noting a strong imperative to understand precipitation extremes, and that considerable
uncertainty affects observational data sets, this paper compares the representation of …

Polynomial chaos expansion of random coefficients and the solution of stochastic partial differential equations in the tensor train format

S Dolgov, BN Khoromskij, A Litvinenko… - SIAM/ASA Journal on …, 2015 - SIAM
We apply the tensor train (TT) decomposition to construct the tensor product polynomial
chaos expansion (PCE) of a random field, to solve the stochastic elliptic diffusion PDE with …

Efficient modeling of spatial extremes over large geographical domains

A Hazra, R Huser, D Bolin - Journal of Computational and …, 2024 - Taylor & Francis
Various natural phenomena exhibit spatial extremal dependence at short spatial distances.
However, existing models proposed in the spatial extremes literature often assume that …