A nonparametric test of conditional autoregressive heteroscedasticity for threshold autoregressive models

被引：0
|
作者：
Chen, M [1 ]
Chen, GM [1 ]
机构：
[1] Chinese Acad Sci, Inst Appl Math, Beijing 100080, Peoples R China
来源：
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE | 2001年 / 29卷 / 04期
关键词：
conditional heteroscedasticity; nonparametric test; threshold autoregressive model;
D O I：
10.2307/3316013
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：
Threshold autoregressive models are widely used in time-series applications. When building or using such a model, it is important to know whether conditional heteroscedasticity exists. The authors propose a nonparametric test of this hypothesis. They develop the large-sample theory of a test of nonlinear conditional heteroscedasticity adapted to nonlinear autoregressive models and study its finite-sample properties through simulations. They also provide percentage points for carrying out this test, which is found to have very good power overall.
引用
收藏
页码：649 / 666
页数：18
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