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Titel:

Pair-copula Bayesian networks

Dokumenttyp:
Zeitungsartikel
Autor(en):
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 (DAGs). 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 the DAG...     »
Stichworte:
Conditional independence test, Copulas, Directed acyclic graphs, Graphical models, PC algorithm, Regular vines
Dewey Dezimalklassifikation:
510 Mathematik
Zeitschriftentitel:
Journal of Computational and Graphical Statistics
Jahr:
2016
Band / Volume:
25
Jahr / Monat:
2016-11
Quartal:
4. Quartal
Monat:
Nov
Heft / Issue:
4
Seitenangaben Beitrag:
1248–1271
Sprache:
en
Volltext / DOI:
doi:10.1080/10618600.2015.1086355
Verlag / Institution:
Taylor & Francis Group
Hinweise:
published online
Status:
Verlagsversion / published
Publikationsdatum:
10.11.2016
TUM Einrichtung:
Lehrstuhl für Mathematische Statistik
Format:
Text
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