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On error bounds for high-dimensional asymptotic distribution of L2-type test statistic for equality of means

Author

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  • Hyodo, Masashi
  • Nishiyama, Takahiro
  • Pavlenko, Tatjana

Abstract

Two new asymptotic approximations for the distribution of Chen and Qin’s statistic are derived and their explicit error bounds are established. The proposed approximations are shown to be far more accurate than the conventional normal limits in large-p-small-n settings which is successfully approved by the numerical experiments.

Suggested Citation

  • Hyodo, Masashi & Nishiyama, Takahiro & Pavlenko, Tatjana, 2020. "On error bounds for high-dimensional asymptotic distribution of L2-type test statistic for equality of means," Statistics & Probability Letters, Elsevier, vol. 157(C).
    • Handle: RePEc:eee:stapro:v:157:y:2020:i:c:s0167715219302834
    DOI: 10.1016/j.spl.2019.108637
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    Cited by:

    1. Zhang, Jin-Ting & Zhu, Tianming, 2022. "A new normal reference test for linear hypothesis testing in high-dimensional heteroscedastic one-way MANOVA," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
    2. Mingxiang Cao & Yuanjing He, 2022. "A high-dimensional test on linear hypothesis of means under a low-dimensional factor model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(5), pages 557-572, July.

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