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Title:

Pair-copula Bayesian networks

Document type:
Zeitschriftenaufsatz
Author(s):
Bauer, A. and Czado, C.
Abstract:
Pair-copula Bayesian networks (PCBNs) are a novel class of multivariate statistical models, which combine the distributional flexibility of pair-copula constructions (PCCs) with the parsimony of conditional independence models associated with directed acyclic graphs (DAG). We are first to provide generic algorithms for random sampling and likelihood inference in arbitrary PCBNs as well as for selecting orderings of the parents of the vertices in the underlying graphs. Model selection of th...     »
Keywords:
conditional independence test; copulas; directed acyclic graphs; graphical models; PC algorithm; regular vines
Journal title:
Preprint
Year:
2012
Reviewed:
ja
Language:
de
Status:
Preprint / submitted
TUM Institution:
Lehrstuhl für Mathematische Statistik
Format:
Text
 BibTeX