6 papers · 1 filter
Directional variograms for multivariate extremes
Manuel Hentschel, Frank Röttger, Johan Segers +1
Multivariate generalized Pareto distributions arise as limits of threshold exceedances and form a central model class for multivariate extremes. Existing inference methods based on…
Spectral Sparsification of Laplacian-Constrained Gaussian and Hüsler-Reiss Graphical Models
Ignacio Echave-Sustaeta RodrÃguez, Aida Abiad, Frank Röttger
Graph Laplacians encode graph structures in matrix form, and thus facilitate the application of linear algebra to graph theory. In statistics, two related families of probabilistic…
Learning Gaussian Graphical Models under Total Positivity via Spectral Graph Sparsification
Ignacio Echave-Sustaeta RodrÃguez, Aida Abiad, Frank Röttger
Many practical data analysis tasks reduce to learning, from observed samples, how a collection of variables depend on each other. A widely used approach is to fit a Gaussian graphi…
Extremes of structural causal models
Sebastian Engelke, Nicola Gnecco, Frank Röttger
The behavior of extreme observations is well-understood for time series or spatial data, but little is known if the data generating process is a structural causal model (SCM). We s…
Latent Gaussian and Hüsler--Reiss Graphical Models with Golazo Penalty
Ignacio Echave-Sustaeta RodrÃguez, Frank Röttger
The existence of latent variables in practical problems is common, for example when some variables are difficult or expensive to measure, or simply unknown. When latent variables a…
Modeling Extreme Events: Univariate and Multivariate Data-Driven Approaches
Gloria Buriticá, Manuel Hentschel, Olivier C. Pasche +2
This article summarizes the contribution of team genEVA to the EVA (2023) Conference Data Challenge. The challenge comprises four individual tasks, with two focused on univariate e…