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Document type:
Zeitungsartikel 
Author(s):
Gruber, L. and Czado, D. 
Title:
Bayesian Model Selection of Regular Vine Copulas 
Abstract:
Regular vine copulas are a flexible class of dependence models, but Bayesian methodology for model selection and inference is not yet fully developed. We propose sparsity-inducing but otherwise non-informative priors, and present novel proposals to enable reversible jump Markov chain Monte Carlo posterior simulation for Bayesian model selection and inference. Our method is the first to jointly estimate the posterior distribution of all trees of a regular vine copula. This represents a substantia...    »
 
Keywords:
multivariate analysis, dependence modeling, copula modeling, vine copulas, Bayesian inference, posterior simulation, importance sampling, simulation studies, financial analysis, risk forecasting 
Dewey Decimal Classification:
510 Mathematik 
Journal title:
Bayesian Analysis 
Year:
2018 
Journal volume:
13 
Year / month:
2018-01 
Quarter:
1. Quartal 
Month:
Jan 
Journal issue:
Pages contribution:
1111-1135 
Fulltext / DOI:
WWW:
_blank 
Publisher:
Int Soc Bayesian Analysis 
Notes:
Published online 
Date of publication:
12.01.2018 
TUM Institution:
Lehrstuhl für Mathematische Statistik 
Format:
Text