Ӧ�ø���ͳ�� 2011, 27(3) 276-282 DOI:      ISSN: 1001-4268 CN: 31-1256

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A Bayesian Thershold Nonlinearity Test for TAR Models
Xia Qiang,Liu Jinshan
South China Agricultural University
Abstract:

Under the hypothesis of normal distribution,
the change-point problems have four cases according to mean and
variance changing. In this paper, we look upon the threshold
nonlinearity test of TAR models as a change-point problem, which has
a change-mean and constant-variance. We adopt reversible-jump Markov
chain Monte Carlo (RJMCMC) methods to calculate the posterior
probabilities of two competitive models, namely AR and TAR models.
Posterior evidence favoring the TAR model indicates threshold
nonlinearity. Simulation experiments demonstrate that our method
works very well in distinguishing AR and TAR models.

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