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Document type:
Zeitungsartikel 
Author(s):
Ngoc Mai Tran, Johannes Buck, Claudia Klüppelberg 
Title:
Estimating a Latent Tree for Extremes 
Abstract:
The Latent River Problem has emerged as a flagship problem for causal discovery in extreme value statistics. This paper gives QTree, a simple and efficient algorithm to solve the Latent River Problem that outperforms existing methods. QTree returns a directed graph and achieves almost perfect recovery on the Upper Danube, the existing benchmark dataset, as well as on new data from the Lower Colorado River in Texas. It can handle missing data, has an automated parameter tuning procedure, and runs...    »
 
Keywords:
causal inference, max-linear, Bayesian networks, extreme values statistics, directed graphical models 
Dewey Decimal Classification:
510 Mathematik 
Journal title:
Preprint 
Year:
2021 
Language:
en 
WWW:
Status:
Preprint / submitted 
TUM Institution:
Lehrstuhl für Mathematische Statistik 
Format:
Text 
Ingested:
23.08.2021