123 citations · 267 across the 30 of their papers we have counts for
6 papers · 1 filter
Total positivity in multivariate extremes
Frank Röttger, Sebastian Engelke, Piotr Zwiernik
Positive dependence is present in many real world data sets and has appealing stochastic properties that can be exploited in statistical modeling and in estimation. In particular,…
Learning extremal graphical structures in high dimensions
Sebastian Engelke, Michaël Lalancette, Stanislav Volgushev
Extremal graphical models encode the conditional independence structure of multivariate extremes. Key statistics for learning extremal graphical structures are empirical extremal v…
Modelling and simulating spatial extremes by combining extreme value theory with generative adversarial networks
Younes Boulaguiem, Jakob Zscheischler, Edoardo Vignotto +2
Modelling dependencies between climate extremes is important for climate risk assessment, for instance when allocating emergency management funds. In statistics, multivariate extre…
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…
Distributionally robust tail bounds based on Wasserstein distance and -divergence
Corina Birghila, Maximilian Aigner, Sebastian Engelke
In this work, we provide robust bounds on the tail probabilities and the tail index of heavy-tailed distributions in the context of model misspecification. They are defined as the…
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…