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Functional test for high-dimensional covariance matrix, with application to mitochondrial calcium concentration

Author

Listed:
  • Tao Zhang

    (Guangxi University of Science and Technology)

  • Zhiwen Wang

    (Guangxi University of Science and Technology)

  • Yanling Wan

    (Guangxi University of Science and Technology)

Abstract

In this paper, we present a novel method to test equality of covariance matrices of two high-dimensional samples. The methodology applies the idea of functional data analysis into high-dimensional data study. Asymptotic results of the proposed method are established. Some simulation studies are conducted to investigate the finite sample performance of the proposed method. We illustrate our testing procedures on a mitochondrial calcium concentration data for testing equality of covariance matrices.

Suggested Citation

  • Tao Zhang & Zhiwen Wang & Yanling Wan, 2021. "Functional test for high-dimensional covariance matrix, with application to mitochondrial calcium concentration," Statistical Papers, Springer, vol. 62(3), pages 1213-1230, June.
    • Handle: RePEc:spr:stpapr:v:62:y:2021:i:3:d:10.1007_s00362-019-01133-8
    DOI: 10.1007/s00362-019-01133-8
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    References listed on IDEAS

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    Cited by:

    1. Jin-Ting Zhang & Bu Zhou & Jia Guo, 2022. "Testing high-dimensional mean vector with applications," Statistical Papers, Springer, vol. 63(4), pages 1105-1137, August.

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