A NEW TEST FOR NORMALITY IN LINEAR AUTOREGRESSIVE MODELS

被引：0
|
作者：
CHEN Min WU Guofu (Institute of Applied Mathematics
机构：
来源：
Journal of Systems Science & Complexity | 2002年 / 04期
基金：
中国国家自然科学基金;
关键词：
Nonparametric test; time-reversibility; one-step forecast; Kolmogorov-Smirnov statistic;
D O I：
暂无
中图分类号：
O211 [概率论（几率论、或然率论）];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
A nonparametric test for normality of linear autoregressive time series is proposed in this paper. The test is based on the best one-step forecast in mean square with time reverse. Some asymptotic theory is developed for the test, and it is shown that the test is easy to use and has good powers. The empirical percentage points to conduct the test in practice are provided and three examples using real data are included.
引用
收藏
页码：423 / 435
页数：13
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