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Title:

Pair-copula constructions for non-Gaussian DAG models

Document type:
Zeitschriftenaufsatz
Author(s):
Bauer, A., Czado, C. and Klein, T.
Abstract:
We propose a new type of multivariate statistical model that permits non-Gaussian distributions as well as the inclusion of conditional independence assumptions induced by a directed acyclic graph. These models feature a specific factorisation of the likelihood that is based on pair-copula constructions and hence involves only univariate distributions and bivariate copulas, of which some may be conditional. We demonstrate maximum-likelihood estimation of the parameters of such models and c...     »
Keywords:
Bayesian networks, conditional independence, copulas, graphical models, likelihood inference, regular vines
Journal title:
The Canadian Journal of Statistics
Year:
2012
Journal volume:
40
Journal issue:
1
Pages contribution:
86 - 109
Reviewed:
ja
Language:
en
Fulltext / DOI:
doi:10.1002/cjs.10131
E-ISSN:
1708-945X
Status:
Erstveröffentlichung
Semester:
WS 11-12
TUM Institution:
Lehrstuhl für Mathematische Statistik
Format:
Text
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