Graphical Models for Extremes

DOI10.1111/rssb.12355OpenAlexW3198883342MaRDI QIDQ5087161

Adrien S. Hitz, Sebastian Engelke

Publication date: 8 July 2022

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1812.01734

zbMATH Keywords

extreme value theorygraphical modelsconditional independencesparsitymultivariate Pareto distribution

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (18)

Causal discovery in heavy-tailed models ⋮ Linking representations for multivariate extremes via a limit set ⋮ Bayesian Spatial Clustering of Extremal Behavior for Hydrological Variables ⋮ Estimating an extreme Bayesian network via scalings ⋮ Total positivity in multivariate extremes ⋮ Tail inverse regression: dimension reduction for prediction of extremes ⋮ A modeler's guide to extreme value software ⋮ Modeling panels of extremes ⋮ Causality in extremes of time series ⋮ Simulating flood event sets using extremal principal components ⋮ Extremal characteristics of conditional models ⋮ Extremes of Markov random fields on block graphs: max-stable limits and structured Hüsler-Reiss distributions ⋮ Subbotin graphical models for extreme value dependencies with applications to functional neuronal connectivity ⋮ Recursive max-linear models with propagating noise ⋮ Rank-based estimation under asymptotic dependence and independence, with applications to spatial extremes ⋮ Extremes and regular variation ⋮ Modeling spatial tail dependence with Cauchy convolution processes ⋮ Conditional independence in max-linear Bayesian networks

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