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 |
Author: | 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. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/4433 |
ISSN: | 1133-0686 |
Publisher Version: | http://www.springerlink.com/content/m546718w62437113/ |
Appears in Collections: | DMat - Artigos |
Files in This Item:
File | Description | Size | Format | |
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artigo.pdf | 207.94 kB | Adobe PDF | View/Open |
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