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Title:

Representing sparse Gaussian DAGs as sparse R-vines allowing for non-Gaussian Dependence

Document type:
Zeitschriftenaufsatz
Author(s):
Müller, D. and Czado C.
Abstract:
Modeling dependence in high dimensional systems has become an increasingly important topic. Most approaches rely on the assumption of a joint Gaussian distribution such as statistical models on directed acyclic graphs (DAGs). They are based on modeling conditional independencies and are scalable to high dimensions. In contrast, vine copula based models can accommodate more elaborate features like tail dependence and asymmetry. This exibility comes however at the cost of exponentially increasin...     »
Keywords:
Graphical Models, Dependence Modeling, Vine Copula
Journal title:
Preprint
Year:
2016
Reviewed:
ja
Language:
en
Fulltext / DOI:
doi:10.1080/10618600.2017.1366911
WWW:
preprint
Status:
Preprint / submitted
TUM Institution:
Lehrstuhl für Mathematische Statistik
Format:
Text
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