Monitoring memory parameter change-points in long-memory time series

被引：0
作者：
Zhanshou Chen
Yanting Xiao
Fuxiao Li
机构：
[1] Qinghai Normal University,School of Mathematics and Statistics
[2] Academy of Plateau Science and Sustainability,Department of Applied Mathematics
[3] Xi’an University of Technology,undefined
来源：
Empirical Economics | 2021年 / 60卷
关键词：
Long-memory process; Change-point monitoring; Sieve bootstrap; Fractional Brownian motion; C12; C15; C22;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, we propose two ratio-type statistics to sequentially detect the memory parameter change-points in the long-memory time series. The limiting distributions of monitoring statistics under the no-change-point null hypothesis as well as their consistency under the alternative hypothesis are proved. In particular, a sieve bootstrap approximation method is proposed to determine the critical values. Extensive simulations indicate that the new monitoring procedures perform well in finite samples. Finally, we illustrate our monitoring procedures by two sets of real data.
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页码：2365 / 2389
页数：24
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