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Testing the equality of multivariate means when $$p>n$$ p > n by combining the Hotelling and Simes tests

Author

Listed:
  • Tzviel Frostig

    (Tel Aviv University)

  • Yoav Benjamini

    (Tel Aviv University)

Abstract

We propose a method of testing a shift between mean vectors of two multivariate Gaussian random variables in a high-dimensional setting incorporating the possible dependency and allowing $$p > n$$ p > n . This method is a combination of two well-known tests: the Hotelling test and the Simes test. The tests are integrated by sampling several dimensions at each iteration, testing each using the Hotelling test, and combining their results using the Simes test. We prove that this procedure is valid asymptotically. This procedure can be extended to handle non-equal covariance matrices by plugging in the appropriate extension of the Hotelling test. Using a simulation study, we show that the proposed test is advantageous over state-of-the-art tests in many scenarios and robust to violation of the Gaussian assumption.

Suggested Citation

  • Tzviel Frostig & Yoav Benjamini, 2022. "Testing the equality of multivariate means when $$p>n$$ p > n by combining the Hotelling and Simes tests," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 390-415, June.
  • Handle: RePEc:spr:testjl:v:31:y:2022:i:2:d:10.1007_s11749-021-00781-z
    DOI: 10.1007/s11749-021-00781-z
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    References listed on IDEAS

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