Sequential Test for Change-Point in Long Memory Process

This paper proposes a modified kernel weighted variance ratio statistic to sequentially detect change-point that shifts from a stationary long memory process to a non-stationary long memory process. The limiting distribution of test statistic under the null hypothesis and its consistency under the a...

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Bibliographic Details
Published in:Mathematical problems in engineering 2022-09, Vol.2022, p.1-6
Main Authors: Jia, Xiuqin, Chen, Zhanshou, Liang, Yan
Format: Article
Language:English
Subjects:
Engineering
Hypotheses
Null hypothesis
Sample size
Simulation
Statistics
Time series
Citations: Items that this one cites
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Summary:This paper proposes a modified kernel weighted variance ratio statistic to sequentially detect change-point that shifts from a stationary long memory process to a non-stationary long memory process. The limiting distribution of test statistic under the null hypothesis and its consistency under the alternative hypothesis are proved. Simulations indicate that the new method has better finite sample performance than the available method in the literature. Finally, we illustrate the new method by a set of U.S. inflation rate data.
ISSN:1024-123X
1563-5147
DOI:10.1155/2022/9057587