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- Publisher Website: 10.1016/j.csda.2023.107855
- Scopus: eid_2-s2.0-85174018058
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Article: An RIHT statistic for testing the equality of several high-dimensional mean vectors under homoskedasticity
| Title | An RIHT statistic for testing the equality of several high-dimensional mean vectors under homoskedasticity |
|---|---|
| Authors | |
| Keywords | Central limit theorem Exact four-moment theorem High-dimensional data analysis Mean vector test |
| Issue Date | 1-Feb-2024 |
| Publisher | Elsevier |
| Citation | Computational Statistics & Data Analysis, 2024, v. 190 How to Cite? |
| Abstract | In this article, the problem of testing the equality of several mean vectors is considered under the homoskedasticity in a high-dimensional setting. A ridgelized Hotelling's T2 test (RIHT) is developed and the asymptotic distributions are derived. By requiring only the conditions on the first four moments of the underlying distribution, the RIHT test can be used to test the mean vector free of population distributions under both p≥n and p |
| Persistent Identifier | http://hdl.handle.net/10722/348485 |
| ISSN | 2023 Impact Factor: 1.5 2023 SCImago Journal Rankings: 1.008 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Zhang, Qiuyan | - |
| dc.contributor.author | Wang, Chen | - |
| dc.contributor.author | Zhang, Baoxue | - |
| dc.contributor.author | Yang, Hu | - |
| dc.date.accessioned | 2024-10-10T00:30:57Z | - |
| dc.date.available | 2024-10-10T00:30:57Z | - |
| dc.date.issued | 2024-02-01 | - |
| dc.identifier.citation | Computational Statistics & Data Analysis, 2024, v. 190 | - |
| dc.identifier.issn | 0167-9473 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/348485 | - |
| dc.description.abstract | <p>In this article, the problem of testing the equality of several mean vectors is considered under the homoskedasticity in a high-dimensional setting. A ridgelized Hotelling's T2 test (RIHT) is developed and the <a href="https://www.sciencedirect.com/topics/biochemistry-genetics-and-molecular-biology/asymptotic-distribution" title="Learn more about asymptotic distributions from ScienceDirect's AI-generated Topic Pages">asymptotic distributions</a> are derived. By requiring only the conditions on the first four moments of the underlying distribution, the RIHT test can be used to test the mean vector free of population distributions under both p≥n and p</p> | - |
| dc.language | eng | - |
| dc.publisher | Elsevier | - |
| dc.relation.ispartof | Computational Statistics & Data Analysis | - |
| dc.subject | Central limit theorem | - |
| dc.subject | Exact four-moment theorem | - |
| dc.subject | High-dimensional data analysis | - |
| dc.subject | Mean vector test | - |
| dc.title | An RIHT statistic for testing the equality of several high-dimensional mean vectors under homoskedasticity | - |
| dc.type | Article | - |
| dc.identifier.doi | 10.1016/j.csda.2023.107855 | - |
| dc.identifier.scopus | eid_2-s2.0-85174018058 | - |
| dc.identifier.volume | 190 | - |
| dc.identifier.eissn | 1872-7352 | - |
| dc.identifier.issnl | 0167-9473 | - |