12 papers
Estimating a Directed Tree for Extremes
Ngoc Mai Tran, Johannes Buck, Claudia Klüppelberg
We propose a new method to estimate a root-directed spanning tree from extreme data. A prominent example is a river network, to be discovered from extreme flow measured at a set of…
Conditional Independence in Max-linear Bayesian Networks
Carlos Améndola, Claudia Klüppelberg, Steffen Lauritzen +1
Motivated by extreme value theory, max-linear Bayesian networks have been recently introduced and studied as an alternative to linear structural equation models. However, for max-l…
Max-linear models in random environment
Claudia Klüppelberg, Ercan Sönmez
We extend previous work of max-linear models on finite directed acyclic graphs to infinite graphs as well as random graphs, and investigate their relations to classical percolation…
Indirect Inference for Lévy-driven continuous-time GARCH models
Thiago do Rêgo Sousa, Stephan Haug, Claudia Klüppelberg
We advocate the use of an Indirect Inference method to estimate the parameter of a COGARCH(1,1) process for equally spaced observations. This requires that the true model can be si…
Smoothing of transport plans with fixed marginals and rigorous semiclassical limit of the Hohenberg-Kohn functional
Codina Cotar, Gero Friesecke, Claudia Klüppelberg
We prove rigorously that the exact N-electron Hohenberg-Kohn density functional converges in the strongly interacting limit to the strictly correlated electrons (SCE) functional, a…
Generalised least squares estimation of regularly varying space-time processes based on flexible observation schemes
Sven Buhl, Claudia Klüppelberg
Regularly varying stochastic processes model extreme dependence between process values at different locations and/or time points. For such processes we propose a two-step parameter…