A Bayesian analysis of generalized threshold autoregressive models

被引：31

作者：

Chen, CWS ^{[1
]}

机构：

[1] Feng Chia Univ, Dept Stat, Taichung 407, Taiwan

来源：

STATISTICS & PROBABILITY LETTERS | 1998年 / 40卷 / 01期

关键词：

MCMC method; Gibbs sampler; metropolis algorithm; generalized TAR models;

D O I：

10.1016/S0167-7152(98)00077-7

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The threshold autoregressive (TAR) model is generalized which results in more flexibility in applications. We construct a Bayesian framework to show that Markov chain Monte Carlo method can be applied to estimating parameters with success. (C) 1998 Elsevier Science B.V. All rights reserved.

引用

收藏

页码：15 / 22

页数：8

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