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Approximate Bayesian methods for multivariate and conditional copulae

Abstract:

We describe a simple method for making inference on a functional of a multivariate distribution. The method is based on a copula representation of the multivariate distribution, where copula is a flexible probabilistic tool that allows the researcher to model the joint distribution of a random vector in two separate steps: the marginal distributions and a copula function which captures the dependence structure among the vector components. The method is also based on the properties of an appro...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
NDM Experimental Medicine
Role:
Author
Publisher:
Springer, Cham Publisher's website
Volume:
456
Pages:
261-268
Series:
Advances in Intelligent Systems and Computing
Publication date:
2016-07-30
Acceptance date:
2016-04-10
DOI:
ISSN:
2194-5357
Pubs id:
pubs:671222
URN:
uri:1f77412c-cd55-4927-b654-d46fbb61f2e4
UUID:
uuid:1f77412c-cd55-4927-b654-d46fbb61f2e4
Local pid:
pubs:671222
ISBN:
9783319429717

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