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Document type:
Zeitschriftenaufsatz 
Author(s):
Alexander Kreuzer, Claudia Czado 
Title:
Efficient Bayesian inference for nonlinear state space models with univariate autoregressive state equation 
Abstract:
Latent autoregressive processes are a popular choice to model time varying parameters. These models can be formulated as nonlinear state space models for which inference is not straightforward due to the high number of parameters. Therefore maximum likelihood methods are often infeasible and researchers rely on alternative techniques, such as Gibbs sampling. But conventional Gibbs samplers are often tailored to specific situations and suffer from high autocorrelation among repeated draws. We pre...    »
 
Keywords:
Asymmetric tail dependence; Copulas; Financial time series; Time varying parameters; Volatility 
Dewey Decimal Classification:
510 Mathematik 
Journal title:
Journal of Computational and Graphical Statistics 
Year:
2020 
Journal volume:
29 
Year / month:
2020-03 
Quarter:
1. Quartal 
Month:
Mar 
Journal issue:
Pages contribution:
523-534 
Language:
en 
Publisher:
Taylor & Francis 
Notes:
Published online: 12 Mar 2020 
Status:
Erstveröffentlichung 
Accepted:
27.01.2020 
Date of publication:
10.03.2020 
Semester:
WS 19-20 
TUM Institution:
Professur für Angewandte Mathematische Statistik 
Format:
Text