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Bayesian Nonparametric Inference for a Multivariate Copula Function

Wu, Juan, Wang, Xue, Walker, Stephen G. (2014) Bayesian Nonparametric Inference for a Multivariate Copula Function. Methodology and Computing in Applied Probability, 16 (3). pp. 747-763. ISSN 1387-5841. (doi:10.1007/s11009-013-9348-5) (KAR id:37428)

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http://dx.doi.org/10.1007/s11009-013-9348-5

Abstract

The paper presents a general Bayesian nonparametric approach

copula, which we then extend to an infinite mixture model. The skew-normal

is developed to draw samples from the correct posterior distribution and the

of the Bayesian nonparametric model is established.

Item Type: Article
DOI/Identification number: 10.1007/s11009-013-9348-5
Uncontrolled keywords: Bayesian nonparametric estimation; copula; infinite mixture skewnormal copula model; Metropolis{Hastings algorithm.
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Xue Wang
Date Deposited: 10 Dec 2013 10:21 UTC
Last Modified: 15 Apr 2020 03:05 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/37428 (The current URI for this page, for reference purposes)
Wang, Xue: https://orcid.org/0000-0002-1592-8704
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