Truncating estimation for the change in stochastic trend with heavy-tailed innovations

被引：1
|
作者：
Qin, Ruibing [1 ]
Tian, Zheng [1 ,2 ]
Jin, Hao [1 ]
机构：
[1] NW Polytech Univ, Dept Appl Math, Xian 710072, Shaanxi, Peoples R China
[2] State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
来源：
STATISTICAL PAPERS | 2011年 / 52卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Change-point estimation; Stochastic trend; Heavy-tails; CHANGE-POINT; UNIT-ROOT; REGRESSION;
D O I：
10.1007/s00362-009-0223-y
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：
A CUSUM estimator is proposed for the change point in stochastic trend with heavy-tailed innovations. In order to avoid the outliers caused by heavy-tailed innovations, we also construct a truncating CUSUM estimator. Results in this paper show that the CUSUM estimators are consistent. Simulations demonstrate that the truncating estimator behaves better for the heavy-tailed innovations.
引用
收藏
页码：203 / 217
页数：15
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