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Steel, Mark F. J. (2008) Bayesian time series analysis. In: Durlauf , S. N. and Blume, L. E., (eds.) The New Palgrave dictionary of economics. Basingstoke, Hampshire ; New York: Palgrave Macmillan. ISBN 9780333786765
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Official URL: http://webcat.warwick.ac.uk/record=b2232914~S1
Abstract
This article describes the use of Bayesian methods in the statistical analysis of time series. The use of Markov chain Monte Carlo methods has made even the more complex time series models amenable to Bayesian analysis. Models discussed in some detail are ARIMA models and their fractionally integrated counterparts, state space models, Markov switching and mixture models, and models allowing for time-varying volatility. A final section reviews some recent approaches to nonparametric Bayesian modelling of time series.
Item Type: | Book Item | ||||
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Subjects: | Q Science > QA Mathematics | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||
Library of Congress Subject Headings (LCSH): | Time-series analysis, Bayesian statistical decision theory | ||||
Publisher: | Palgrave Macmillan | ||||
Place of Publication: | Basingstoke, Hampshire ; New York | ||||
ISBN: | 9780333786765 | ||||
Book Title: | The New Palgrave dictionary of economics | ||||
Editor: | Durlauf , S. N. and Blume, L. E. | ||||
Official Date: | 2008 | ||||
Dates: |
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Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Description: | 2nd edition |
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