123 citations · 267 across the 30 of their papers we have counts for
15 papers · 1 filter
Asymmetric dependence in hydrological extremes
Cristina Deidda, Sebastian Engelke, Carlo De Michele
Extremal dependence describes the strength of correlation between the largest observations of two variables. It is usually measured with symmetric dependence coefficients that do n…
Statistical Inference for Hüsler-Reiss Graphical Models Through Matrix Completions
Manuel Hentschel, Sebastian Engelke, Johan Segers
The severity of multivariate extreme events is driven by the dependence between the largest marginal observations. The Hüsler-Reiss distribution is a versatile model for this extre…
Neural Networks for Extreme Quantile Regression with an Application to Forecasting of Flood Risk
Olivier C. Pasche, Sebastian Engelke
Risk assessment for extreme events requires accurate estimation of high quantiles that go beyond the range of historical observations. When the risk depends on the values of observ…
Modeling panels of extremes
Debbie J. Dupuis, Sebastian Engelke, Luca Trapin
Extreme value applications commonly employ regression techniques to capture cross-sectional heterogeneity or time-variation in the data. Estimation of the parameters of an extreme…
Extremal Random Forests
Nicola Gnecco, Edossa Merga Terefe, Sebastian Engelke
Classical methods for quantile regression fail in cases where the quantile of interest is extreme and only few or no training data points exceed it. Asymptotic results from extreme…
Estimation and Inference of Extremal Quantile Treatment Effects for Heavy-Tailed Distributions
David Deuber, Jinzhou Li, Sebastian Engelke +1
Causal inference for extreme events has many potential applications in fields such as climate science, medicine and economics. We study the extremal quantile treatment effect of a…
Gradient boosting for extreme quantile regression
Jasper Velthoen, Clément Dombry, Juan-Juan Cai +1
Extreme quantile regression provides estimates of conditional quantiles outside the range of the data. Classical quantile regression performs poorly in such cases since data in the…
Structure learning for extremal tree models
Sebastian Engelke, Stanislav Volgushev
Extremal graphical models are sparse statistical models for multivariate extreme events. The underlying graph encodes conditional independencies and enables a visual interpretation…
Sparse Structures for Multivariate Extremes
Sebastian Engelke, Jevgenijs Ivanovs
Extreme value statistics provides accurate estimates for the small occurrence probabilities of rare events. While theory and statistical tools for univariate extremes are well-deve…
Causal discovery in heavy-tailed models
Nicola Gnecco, Nicolai Meinshausen, Jonas Peters +1
Causal questions are omnipresent in many scientific problems. While much progress has been made in the analysis of causal relationships between random variables, these methods are…
Extremal Behavior of Aggregated Data with an Application to Downscaling
Sebastian Engelke, Raphael de Fondeville, Marco Oesting
The distribution of spatially aggregated data from a stochastic process may exhibit a different tail behavior than its marginal distributions. For a large class of aggregating…
Bayesian inference for multivariate extreme value distributions
Clement Dombry, Sebastian Engelke, Marco Oesting
Statistical modeling of multivariate and spatial extreme events has attracted broad attention in various areas of science. Max-stable distributions and processes are the natural cl…
Exact simulation of max-stable processes
Clément Dombry, Sebastian Engelke, Marco Oesting
Max-stable processes play an important role as models for spatial extreme events. Their complex structure as the pointwise maximum over an infinite number of random functions makes…
Extremes on river networks
Peiman Asadi, Anthony C. Davison, Sebastian Engelke
Max-stable processes are the natural extension of the classical extreme-value distributions to the functional setting, and they are increasingly widely used to estimate probabiliti…
Estimation of Huesler-Reiss distributions and Brown-Resnick processes
Sebastian Engelke, Alexander Malinowski, Zakhar Kabluchko +1
Estimation of extreme-value parameters from observations in the max-domain of attraction (MDA) of a multivariate max-stable distribution commonly uses aggregated data such as block…