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Document type:
Zeitungsartikel 
Author(s):
Klüppelberg, C. and Krali, M. 
Title:
Estimating an Extreme Bayesian Network via Scalings 
Abstract:
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 graph and some exogenous innovation. Motivated by extreme value theory, innovations are assumed to have regularly varying distribution tails. We propose a scaling technique in order to determine a causal order of the node variables. All dependence parameters are then estimated from the estimated scalings. Furthermore, we...    »
 
Keywords:
causal order, directed acyclic graph, extreme value statistics, graphical model, recursive max-linear model, regular variation, structural equation model, structure learning 
Dewey Decimal Classification:
510 Mathematik 
Journal title:
Preprint 
Year:
2019 
Language:
en 
WWW:
Status:
Preprint / submitted 
TUM Institution:
Lehrstuhl für Mathematische Statistik 
Format:
Text