# Journal article

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

Abstract:

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...

Publication status:
Published

### Authors

More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
Journal:
JOURNAL OF TIME SERIES ANALYSIS
Volume:
25
Issue:
6
Pages:
785-809
Publication date:
2004-11-01
DOI:
EISSN:
1467-9892
ISSN:
0143-9782
Language:
English
Keywords:
Pubs id:
pubs:190592
UUID:
uuid:0ace09b3-33e4-4869-8549-0cf4e8e92c00
Local pid:
pubs:190592
Source identifiers:
190592
Deposit date:
2012-12-19