This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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39
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Type:
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Contributed
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Date/Time:
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Sunday, August 1, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Computing
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| Abstract - #307081 |
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Title:
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Using the RJMCMC Procedure for Identifying and Estimating Univariate TAR Models
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Author(s):
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Fabio Humberto Nieto*+ and Hanwen Zhang and Wen Li
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Companies:
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Universidad Nacional de Colombia and Santo Tomás University and Iowa State University
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Address:
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Carrera 30 No. 45-03, Bogotá, 0000, Colombia
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Keywords:
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Bayesian model choice ;
Nonlinear time series ;
RJMCMC sampler ;
Threshold autoregressive (TAR) models
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Abstract:
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One way that has been used for identifying and estimating threshold autoregressive (TAR) models for nonlinear time series follows the MCMC approach via the Gibbs sampler. This route has major computational difficulties, specifically, in getting convergence to the parameter distributions. In this paper, a new procedure for identifying a TAR model and for estimating its parameters is developed, following the RJMCMC sampler. It is found that the proposed procedure conveys a Markov chain with converegence properties.
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