Griffin, J.E. and Steel, Mark F.J. (2011) Stick-Breaking Autoregressive Processes. Journal of Econometrics, 162 (2). pp. 383-396. ISSN 0304-4076.
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| Official URL http://dx.doi.org/10.1016/j.jeconom.2011.03.001 |
Abstract
This paper considers the problem of defining a time-dependent nonparametric prior for use in Bayesian nonparametric modelling of time series. A recursive construction allows the definition of priors whose marginals have a general stick-breaking form. The processes with Poisson–Dirichlet and Dirichlet process marginals are investigated in some detail. We develop a general conditional Markov Chain Monte Carlo (MCMC) method for inference in the wide subclass of these models where the parameters of the marginal stick-breaking process are nondecreasing sequences. We derive a generalised Pólya urn scheme type representation of the Dirichlet process construction, which allows us to develop a marginal MCMC method for this case. We apply the proposed methods to financial data to develop a semi-parametric stochastic volatility model with a time-varying nonparametric returns distribution. Finally, we present two examples concerning the analysis of regional GDP and its growth.
| Item Type: | Article |
|---|---|
| Uncontrolled keywords: | Bayesian nonparametrics; Dirichlet process; Poisson–Dirichlet process; Time-dependent nonparametrics |
| Subjects: | Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
| Divisions: | Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics |
| Depositing User: | Jim Griffin |
| Date Deposited: | 30 May 2012 10:01 |
| Last Modified: | 06 Jun 2012 11:20 |
| Resource URI: | http://kar.kent.ac.uk/id/eprint/29591 (The current URI for this page, for reference purposes) |
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