Bootstrap unit root test based on least absolute deviation estimation under dependence assumptions

被引：1
|
作者：
Yang, Xiaorong [1 ]
机构：
[1] Zhejiang Gongshang Univ, Coll Stat & Math, Hangzhou 310018, Peoples R China
来源：
JOURNAL OF APPLIED STATISTICS | 2015年 / 42卷 / 06期
基金：
国家教育部科学基金资助;
关键词：
least absolute deviation; unit root; bootstrap; dependent random variables; autoregressive processes; 60F05; 62F40; WEAK-CONVERGENCE; STOCHASTIC INTEGRALS; MOMENT INEQUALITIES; ASYMPTOTIC THEORY; LIMIT THEORY;
D O I：
10.1080/02664763.2014.999652
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：
In this paper, a bootstrap test based on the least absolute deviation (LAD) estimation for the unit root test in first-order autoregressive models with dependent residuals is considered. The convergence in probability of the bootstrap distribution function is established. Under the frame of dependence assumptions, the asymptotic behavior of the bootstrap LAD estimator is independent of the covariance matrix of the residuals, which automatically approximates the target distribution.
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页码：1332 / 1347
页数：16
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