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A high-dimensional test on linear hypothesis of means under a low-dimensional factor model

Author

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  • Mingxiang Cao

    (Anhui Normal University)

  • Yuanjing He

    (Anhui Technical College of Industry and Economy)

Abstract

In this paper, the problem of testing the hypothesis of linear combination of k-sample means of high-dimensional data is investigated under a low-dimensional factor model. We propose a new test and derive that the asymptotic distribution of the test statistic is a weighted distribution of independent chi-squared distribution of 1 degree of freedom under the null hypothesis and mild conditions. We provide numerical studies on both sizes and powers to illustrate performance of the proposed test.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:metrik:v:85:y:2022:i:5:d:10.1007_s00184-021-00841-2
    DOI: 10.1007/s00184-021-00841-2
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    References listed on IDEAS

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