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Document type:
Zeitungsartikel 
Author(s):
Kreuzer, A. and Czado, C. 
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...    »
 
Dewey Decimal Classification:
510 Mathematik 
Journal title:
Preprint 
Year:
2019 
WWW:
Status:
Preprint / submitted 
TUM Institution:
Professur für Angewandt Mathematische Statistik 
Format:
Text 
Ingested:
27.02.2019