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Construction of stationary time series via the Gibbs sampler with application to volatility models

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Pitt, Michael K. and Walker, S. G. (Stephen G.) (2001) Construction of stationary time series via the Gibbs sampler with application to volatility models. Working Paper. Coventry: University of Warwick, Department of Economics. Warwick economic research papers (No.595).

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Abstract

In this paper, we provide a method for modelling stationary time series. We allow the family of marginal densities for the observations to be specified. Our approach is to construct the model with a specified marginal family and build the dependence structure around it. We show that the resulting time series is linear with a simple autocorrelation structure. In particular, we present an original application of the Gibbs sampler. We illustrate our approach by fitting a model to time series count data with a marginal Poisson-gamma density.

Item Type: Working or Discussion Paper (Working Paper)
Subjects: H Social Sciences > HB Economic Theory
Q Science > QA Mathematics
Divisions: Faculty of Social Sciences > Economics
Library of Congress Subject Headings (LCSH): Markov processes, Monte Carlo method, Probabilities, Stochastic processes
Series Name: Warwick economic research papers
Publisher: University of Warwick, Department of Economics
Place of Publication: Coventry
Official Date: 2001
Dates:
DateEvent
2001Published
Number: No.595
Number of Pages: 31
Status: Not Peer Reviewed
Access rights to Published version: Open Access (Creative Commons)

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