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 Bayesian prediction in threshold autoregressive models with exponential white noise
Please use this identifier to cite or link to this item http://hdl.handle.net/10773/4433

title: Bayesian prediction in threshold autoregressive models with exponential white noise
authors: Pereira, IMS
Amaral-Turkman, MA
keywords: Threshold model
Bayesian prediction
Gibbs sampler
issue date: 2004
publisher: Springer Verlag
abstract: In this paper, we develop a Bayesian analysis of a threshold antoregressive model with exponential noise. An approximate Bayes methodology, which is introduced here; and the Gibbs sampler are used to compute marginal posterior densities for the parameters of the model; including the threshold parameter, and to compute one-step-ahead predictive density functions. The proposed methodology is illustrated with a simulation study and a real example.
URI: http://hdl.handle.net/10773/4433
ISSN: 1133-0686
publisher version/DOI: http://www.springerlink.com/content/m546718w62437113/
source: TEST
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