4 citations · 11 across the 14 of their papers we have counts for
8 papers · 1 filter
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…
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…