Spatial-sign-based high-dimensional white noises test
In this study, we explore the problem of hypothesis testing for white noise in high-dimensional settings, where the dimension of the random vector may exceed the sample sizes. We introduce a test procedure based on spatial-sign for high-dimensional white noise testing. This new spatial-sign-based te...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-10-01
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| Series: | Statistical Theory and Related Fields |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/24754269.2024.2363715 |
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| author | Ping Zhao Dachuan Chen Zhaojun Wang |
| author_facet | Ping Zhao Dachuan Chen Zhaojun Wang |
| author_sort | Ping Zhao |
| collection | DOAJ |
| description | In this study, we explore the problem of hypothesis testing for white noise in high-dimensional settings, where the dimension of the random vector may exceed the sample sizes. We introduce a test procedure based on spatial-sign for high-dimensional white noise testing. This new spatial-sign-based test statistic is designed to emulate the test statistic proposed by Paindaveine and Verdebout [(2016). On high-dimensional sign tests. Bernoulli, 22(3), 1745–1769.], but under a more generalized scatter matrix assumption. We establish the asymptotic null distribution and provide the asymptotic relative efficiency of our test in comparison with the test proposed by Feng et al. [(2022). Testing for high-dimensional white noise. arXiv:2211.02964.] under certain specific alternative hypotheses. Simulation studies further validate the efficiency and robustness of our test, particularly for heavy-tailed distributions. |
| format | Article |
| id | doaj-art-47ececa235864c29b1b39bb6ea8be0b2 |
| institution | OA Journals |
| issn | 2475-4269 2475-4277 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Statistical Theory and Related Fields |
| spelling | doaj-art-47ececa235864c29b1b39bb6ea8be0b22025-08-20T02:33:54ZengTaylor & Francis GroupStatistical Theory and Related Fields2475-42692475-42772024-10-018425126110.1080/24754269.2024.2363715Spatial-sign-based high-dimensional white noises testPing Zhao0Dachuan Chen1Zhaojun Wang2School of Statistics and Data Science, KLMDASR, LEBPS, and LPMC, Nankai University, Nankai District, Tianjin, People's Republic of ChinaSchool of Statistics and Data Science, KLMDASR, LEBPS, and LPMC, Nankai University, Nankai District, Tianjin, People's Republic of ChinaSchool of Statistics and Data Science, KLMDASR, LEBPS, and LPMC, Nankai University, Nankai District, Tianjin, People's Republic of ChinaIn this study, we explore the problem of hypothesis testing for white noise in high-dimensional settings, where the dimension of the random vector may exceed the sample sizes. We introduce a test procedure based on spatial-sign for high-dimensional white noise testing. This new spatial-sign-based test statistic is designed to emulate the test statistic proposed by Paindaveine and Verdebout [(2016). On high-dimensional sign tests. Bernoulli, 22(3), 1745–1769.], but under a more generalized scatter matrix assumption. We establish the asymptotic null distribution and provide the asymptotic relative efficiency of our test in comparison with the test proposed by Feng et al. [(2022). Testing for high-dimensional white noise. arXiv:2211.02964.] under certain specific alternative hypotheses. Simulation studies further validate the efficiency and robustness of our test, particularly for heavy-tailed distributions.https://www.tandfonline.com/doi/10.1080/24754269.2024.2363715High-dimensional dataspatial-signwhite noise test |
| spellingShingle | Ping Zhao Dachuan Chen Zhaojun Wang Spatial-sign-based high-dimensional white noises test Statistical Theory and Related Fields High-dimensional data spatial-sign white noise test |
| title | Spatial-sign-based high-dimensional white noises test |
| title_full | Spatial-sign-based high-dimensional white noises test |
| title_fullStr | Spatial-sign-based high-dimensional white noises test |
| title_full_unstemmed | Spatial-sign-based high-dimensional white noises test |
| title_short | Spatial-sign-based high-dimensional white noises test |
| title_sort | spatial sign based high dimensional white noises test |
| topic | High-dimensional data spatial-sign white noise test |
| url | https://www.tandfonline.com/doi/10.1080/24754269.2024.2363715 |
| work_keys_str_mv | AT pingzhao spatialsignbasedhighdimensionalwhitenoisestest AT dachuanchen spatialsignbasedhighdimensionalwhitenoisestest AT zhaojunwang spatialsignbasedhighdimensionalwhitenoisestest |