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Titel:

Bayesian Model Selection of Regular Vine Copulas

Dokumenttyp:
Zeitungsartikel
Autor(en):
Gruber, L. and Czado, D.
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...     »
Stichworte:
multivariate analysis, dependence modeling, copula modeling, vine copulas, Bayesian inference, posterior simulation, importance sampling, simulation studies, financial analysis, risk forecasting
Dewey Dezimalklassifikation:
510 Mathematik
Zeitschriftentitel:
Bayesian Analysis
Jahr:
2018
Band / Volume:
13
Jahr / Monat:
2018-01
Quartal:
1. Quartal
Monat:
Jan
Heft / Issue:
4
Seitenangaben Beitrag:
1111-1135
Volltext / DOI:
doi:10.1214/17-BA1089
Verlag / Institution:
Int Soc Bayesian Analysis
Hinweise:
Published online
Publikationsdatum:
12.01.2018
TUM Einrichtung:
Lehrstuhl für Mathematische Statistik
Format:
Text
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