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stat.ME2019
Estimating an Extreme Bayesian Network via Scalings
Claudia Klüppelberg, Mario Krali
Recursive max-linear vectors model causal dependence between its components by expressing each node variable as a max-linear function of its parental nodes in a directed acyclic gr…
math.PR2019
Tail probabilities of random linear functions of regularly varying random vectors
Bikramjit Das, Vicky Fasen-Hartmann, Claudia Klüppelberg
We provide a new extension of Breiman's Theorem on computing tail probabilities of a product of random variables to a multivariate setting. In particular, we give a complete charac…
math.ST2019
Identifiability and estimation of recursive max-linear models
Nadine Gissibl, Claudia Klüppelberg, Steffen Lauritzen
We address the identifiablity and estimation of recursive max-linear structural equation models represented by an edge weighted directed acyclic graph (DAG). Such models are genera…