| 基于贝叶斯推断的TAR模型的门限非线性检验 |
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| 引用本文： | 夏强,刘金山.基于贝叶斯推断的TAR模型的门限非线性检验[J].应用概率统计,2011,27(3). |
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| 作者姓名： | 夏强 刘金山 |
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| 作者单位： | 华南农业大学理学院,广州,510642 |
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| 摘 要： | 在正态分布的假定下,变点问题按照均值和方差的变化有四种情形.本文把TAR模型门限非线性的检验问题,看作是对应均值变化,方差不变情形下的变点问题.然后利用可逆跳马尔可夫蒙特卡罗模拟(RJMCMC)方法计算两个比较模型(AR和TAR模型)的后验概率.后验概率的结果支持TAR模型表明门限非线性的存在.模拟实验的结果说明基于贝叶斯推断的检验方法可以很好的区分AR和TAR模型.
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| 关 键 词： | 贝叶斯推断 后验概率 AR模型 RJMCMC TAR模型 |
A Bayesian Thershold Nonlinearity Test for TAR Models |
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| XIA QIANG,LIU JINSHAN.A Bayesian Thershold Nonlinearity Test for TAR Models[J].Chinese Journal of Applied Probability and Statisties,2011,27(3). |
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| Authors: | XIA QIANG LIU JINSHAN |
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| Institution: | Xia Qiang Liu Jinshan(College of Sciences,South China Agricultural University,Guangzhou,510642) |
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| 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.Simulati... |
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| Keywords: | Bayesian inference posterior probability AR model RJMCMC TAR model |
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