Reversible jump Markov chain Monte Carlo strategies for Bayesian model selection in autoregressive processes

Journal article

This paper addresses the problem of Bayesian inference in autoregressive (AR) processes in the case where the correct model order is unknown. Original hierarchical prior models that allow the stationarity of the model to be enforced are proposed. Obtaining the quantities of interest, such as parameter estimates, predictions of future values of the time series, posterior model-order probabilities, etc., requires integration with respect to the full posterior distribution, an operation which is...

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Authors: Vermaak, J; Andrieu, C; Doucet, A; Godsill, S

• Publication status: Published
• Journal: JOURNAL OF TIME SERIES ANALYSIS
• Volume: 25
• Issue: 6
• Pages: 785-809
• Publication date: 2004-11-01
• DOI: 10.1111/j.1467-9892.2004.00380.x
• EISSN: 1467-9892
• ISSN: 0143-9782
• Language: English
• Keywords: Bayesian estimation; Markov chain Monte Carlo; autoregressive process; model selection