A two-sample test for high-dimensional mean vectors via double verification

Ruizhe Jiang (), Xiaowen Huang () and Yunlu Jiang ()
Additional contact information
Ruizhe Jiang: Jinan University
Xiaowen Huang: Jinan University
Yunlu Jiang: Jinan University

Statistical Papers, 2025, vol. 66, issue 6, No 5, 24 pages

Abstract: Abstract Testing the equality of two high-dimensional mean vectors is a fundamental and important statistical problem. The majority of existing methodological frameworks are limited to either dense or sparse cases. In this paper, we propose a novel framework that incorporates a double validation test statistic designed to be valid for both dense and sparse alternatives by combining the test statistic via the random integration of the difference technique and the extreme-type test statistic. The new framework enables a more tailored and efficient process, contingent on the specific circumstances. Additionally, we propose a data-driven procedure for selecting weight to increase the power of the proposed test. Furthermore, we show the asymptotic properties of the proposed test. Numerical simulations and a real data analysis illustrate the promising performances of our proposed approach.

Keywords: High-dimensional two-sample mean test; Double verification test; Data-driven (search for similar items in EconPapers)
Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s00362-025-01744-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:stpapr:v:66:y:2025:i:6:d:10.1007_s00362-025-01744-4

Ordering information: This journal article can be ordered from
http://www.springer. ... business/journal/362

DOI: 10.1007/s00362-025-01744-4

Access Statistics for this article

Statistical Papers is currently edited by C. Müller, W. Krämer and W.G. Müller

More articles in Statistical Papers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().