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

  • Tao Zhang
  • Zhiwen Wang
  • Yanling WanEmail author
Regular Article


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.


High-dimensional data Functional data analysis Significance test Covariance matrix 



T. Zhang’s research was supported by National Natural Science Foundation of China (11561006, 11861014) and Natural Science Foundation of Guangxi (2018JJA110013); Z. Wang’s research was supported by National Natural Science Foundation of China (61462008), Scientific Research and Technology Development Project of Liuzhou (2016C050205) and 2015 Innovation Team Project of Guangxi University of Science and Technology (gxkjdx201504).


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of ScienceGuangxi University of Science and TechnologyLiuzhouChina
  2. 2.School of Computer Science and Communication EngineeringGuangxi University of Science and TechnologyLiuzhouChina
  3. 3.School of Social SciencesGuangxi University of Science and TechnologyLiuzhouChina

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