基于贝叶斯推断的TAR模型的门限非线性检验

摘要

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.%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.