10 papers
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…
Algebraic statistics of Hüsler-Reiss graphical models in multivariate extremes
Carlos Améndola, Jane Ivy Coons, Alexandros Grosdos +1
The field of extreme value statistics is concerned with modeling and predicting rare events. In a Hüsler-Reiss graphical model, a graph represents extremal conditional independenc…
Extremal conditional independence for Hüsler-Reiss distributions via modular functions
Karel Devriendt, Ignacio Echave-Sustaeta RodrÃguez, Frank Röttger
We study extremal conditional independence for Hüsler-Reiss distributions, which is a parametric subclass of multivariate Pareto distributions. As the main contribution, we introd…
Optimal designs for discrete choice models via graph Laplacians
Frank Röttger, Thomas Kahle, Rainer Schwabe
In discrete choice experiments, the information matrix depends on the model parameters. Therefore designing optimally informative experiments for arbitrary initial parameters often…