Hypothesis testing for high-dimensional time series via self-normalization-Reference-Cited by-同舟云学术

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Hypothesis testing for high-dimensional time series via self-normalization

Published:2020-10-01 Issue:5 Volume:48 Page:
ISSN:0090-5364
Container-title:The Annals of Statistics
language:
Short-container-title:Ann. Statist.

Author:

Wang Runmin,Shao Xiaofeng

Publisher

Institute of Mathematical Statistics

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://projecteuclid.org/download/pdfview_1/euclid.aos/1600480930

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Frequency-Domain Test for Multivariate White Noise;Journal of Statistical Theory and Practice;2024-04-01

2. ℓ2 inference for change points in high-dimensional time series via a Two-Way MOSUM;The Annals of Statistics;2024-04-01

3. Kolmogorov–Smirnov type testing for structural breaks: A new adjusted-range based self-normalization approach;Journal of Econometrics;2024-01

4. Two-sample and change-point inference for non-Euclidean valued time series;Electronic Journal of Statistics;2024-01-01

5. Dating the break in high-dimensional data;Bernoulli;2023-11-01

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