$\ell^2$ Inference for Change Points in High-Dimensional Time Series via a Two-Way MOSUM Article Swipe
J. Jenny Li
,
Likai Chen
,
Ning Wang
,
Wei Biao Wu
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2208.13074
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2208.13074
We propose an inference method for detecting multiple change points in high-dimensional time series, targeting dense or spatially clustered signals. Our method aggregates moving sum (MOSUM) statistics cross-sectionally by an $\ell^2$-norm and maximizes them over time. We further introduce a novel Two-Way MOSUM, which utilizes spatial-temporal moving regions to search for breaks, with the added advantage of enhancing testing power when breaks occur in only a few groups. The limiting distribution of an $\ell^2$-aggregated statistic is established for testing break existence by extending a high-dimensional Gaussian approximation theorem to spatial-temporal non-stationary processes. Simulation studies exhibit promising performance of our test in detecting non-sparse weak signals. Two applications, analyzing equity returns and COVID-19 cases in the United States, showcase the real-world relevance of our proposed algorithms.
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- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2208.13074
- https://arxiv.org/pdf/2208.13074
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4293790416
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- OpenAlex ID
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https://openalex.org/W4293790416Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2208.13074Digital Object Identifier
- Title
-
$\ell^2$ Inference for Change Points in High-Dimensional Time Series via a Two-Way MOSUMWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-08-27Full publication date if available
- Authors
-
J. Jenny Li, Likai Chen, Ning Wang, Wei Biao WuList of authors in order
- Landing page
-
https://arxiv.org/abs/2208.13074Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2208.13074Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2208.13074Direct OA link when available
- Concepts
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Inference, Scan statistic, Series (stratigraphy), Algorithm, Statistic, Computer science, Test statistic, Gaussian, Mathematics, Statistical inference, Statistical hypothesis testing, Statistics, Artificial intelligence, Physics, Biology, Quantum mechanics, PaleontologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| sustainable_development_goals[0].score | 0.44999998807907104 |
| sustainable_development_goals[0].display_name | Partnerships for the goals |
| citation_normalized_percentile |