ℓ2 inference for change points in high-dimensional time series via a Two-Way MOSUM
Author:
Affiliation:
1. Department of Statistics and Data Science, Washington University in St. Louis
2. Faculty of Economics and Business, University of Groningen
3. Department of Statistics, University of Chicago
Publisher
Institute of Mathematical Statistics
Reference58 articles.
1. Wu, W. B. and Zhao, Z. (2007). Inference of trends in time series. J. R. Stat. Soc. Ser. B. Stat. Methodol. 69 391–410.
2. CHERNOZHUKOV, V., CHETVERIKOV, D. and KOIKE, Y. (2023). Nearly optimal central limit theorem and bootstrap approximations in high dimensions. Ann. Appl. Probab. 33 2374–2425.
3. Eichinger, B. and Kirch, C. (2018). A MOSUM procedure for the estimation of multiple random change points. Bernoulli 24 526–564.
4. Olshen, A. B., Venkatraman, E. S., Lucito, R. and Wigler, M. (2004). Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics 5 557–572.
5. Wu, W. B. (2005). Nonlinear system theory: Another look at dependence. Proc. Natl. Acad. Sci. USA 102 14150–14154.
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