4 citations · 11 across the 14 of their papers we have counts for
16 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 Rodríguez, 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 Rodríguez, 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 independence…
Extremal conditional independence for Hüsler-Reiss distributions via modular functions
Karel Devriendt, Ignacio Echave-Sustaeta Rodríguez, 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 introdu…
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 Rodríguez, 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…
Graphical models for multivariate extremes
Sebastian Engelke, Manuel Hentschel, Michaël Lalancette +1
Graphical models in extremes have emerged as a diverse and quickly expanding research area in extremal dependence modeling. They allow for parsimonious statistical methodology and…
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…
Parametric and nonparametric symmetries in graphical models for extremes
Frank Röttger, Jane Ivy Coons, Alexandros Grosdos
Colored graphical models provide a parsimonious approach to modeling high-dimensional data by exploiting symmetries in the model parameters. In this work, we introduce the notion o…
On the local metric property in multivariate extremes
Frank Röttger, Quentin Schmitz
Many multivariate data sets exhibit a form of positive dependence, which can either appear globally between all variables or only locally within particular subgroups. A popular not…
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…
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,…
The geometry of Gaussian double Markovian distributions
Tobias Boege, Thomas Kahle, Andreas Kretschmer +1
Gaussian double Markovian models consist of covariance matrices constrained by a pair of graphs specifying zeros simultaneously in the covariance matrix and its inverse. We study t…
Reciprocal Maximum Likelihood Degrees of Brownian Motion Tree Models
Tobias Boege, Jane Ivy Coons, Christopher Eur +2
We give an explicit formula for the reciprocal maximum likelihood degree of Brownian motion tree models. To achieve this, we connect them to certain toric (or log-linear) models, a…
Asymptotics of a locally dependent statistic on finite reflection groups
Frank Röttger
This paper discusses the asymptotic behaviour of the number of descents in a random signed permutation and its inverse, which was posed as an open problem by Chatterjee and Diaconi…