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Title:

Bayesian Multivariate Nonlinear State Space Copula Models

Document type:
Zeitungsartikel
Author(s):
Kreuzer, A., Dalla Valle, L. and Czado, C.
Abstract:
In this paper we propose a flexible class of multivariate nonlinear non-Gaussian state space models, based on copulas. More precisely, we assume that the observation equation and the state equation are defined by copula families that are not necessarily equal. For each time point, the resulting model can be described by a C-vine copula truncated after the first tree, where the root node is represented by the latent state. Inference is performed within the Bayesian framework, using the Hamiltonia...     »
Keywords:
Time Series, Bayesian Inference, Hamiltonian Monte Carlo, Vine Copulas
Dewey Decimal Classification:
510 Mathematik
Journal title:
Preprint
Year:
2019
Language:
en
Status:
Preprint / submitted
TUM Institution:
Professur für Angewandte Mathematische Statistik
Format:
Text
Ingested:
01.11.2019
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