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A revisit to Bai–Saranadasa's two-sample test

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  • Jin-Ting Zhang
  • Tianming Zhu

Abstract

Bai–Saranadasa's two-sample test for high-dimensional data, namely BS-test, has been widely cited in the literature. However, it may not control the size well when the required conditions are not satisfied. In this paper, a revisit to the BS-test is conducted. It is shown that under some regularity conditions and the null hypothesis, the BS-test statistic and a chi-square-type mixture have the same limiting distribution. It is then natural to approximate the null distribution of the BS-test using that of the chi-square-type mixture, which is actually obtained from the BS-test statistic when the two high-dimensional samples are normally distributed. The resulting test is then referred to as a normal-reference test. Two simulation studies and a real data example demonstrate that in terms of size control, the proposed normal-reference test performs very well and it performs substantially better than the BS-test and three other existing competitors proposed in the literature.

Suggested Citation

  • Jin-Ting Zhang & Tianming Zhu, 2022. "A revisit to Bai–Saranadasa's two-sample test," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 34(1), pages 58-76, January.
    • Handle: RePEc:taf:gnstxx:v:34:y:2022:i:1:p:58-76
    DOI: 10.1080/10485252.2021.2015768
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