Bayesian inference for Hidden Markov Model

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Bayesian inference for Hidden Markov Model

Author Info

Rosella Castellano (University of Macerata)
Luisa Scaccia (University of Macerata)

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Rosella Castellano

Abstract

Hidden Markov Models can be considered an extension of mixture models, allowing for

dependent observations. In a hierarchical Bayesian framework, we show how Reversible

Jump Markov Chain Monte Carlo techniques can be used to estimate the parameters of a

model, as well as the number of regimes. We consider a mixture of normal distributions

characterized by different means and variances under each regime, extending the model

proposed by Robert et al. (2000), based on a mixture of zero mean normal distributions.

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Paper provided by Macerata University, Department of Finance and Economic Sciences in its series Working Papers with number 43-2007.

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Date of creation: Oct 2007
Date of revision: Oct 2008
Handle: RePEc:mcr:wpdief:wpaper00043

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This paper has been announced in the following NEP Reports:

NEP-ALL-2008-11-25 (All new papers)
NEP-ECM-2008-11-25 (Econometrics)

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

Billio, M. & Monfort, A. & Robert, C. P., 1999. "Bayesian estimation of switching ARMA models," Journal of Econometrics, Elsevier, vol. 93(2), pages 229-255, December. [Downloadable!] (restricted)
Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November. [Downloadable!] (restricted)
Peter J. Green, 2001. "Modelling Heterogeneity With and Without the Dirichlet Process," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association and Swedish Statistical Association, vol. 28(2), pages 355-375. [Downloadable!] (restricted)
Engel, Charles & Hamilton, James D, 1990. "Long Swings in the Dollar: Are They in the Data and Do Markets Know It?," American Economic Review, American Economic Association, vol. 80(4), pages 689-713, September. [Downloadable!] (restricted)
Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March. [Downloadable!] (restricted)

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