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Multivariate nonparametric tests for independence

Author

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  • Sinha, Bimal Kumar
  • Wieand, H. S.

Abstract

Multivariate generalizations of Bhuchongkul's bivariate rank statistics [Ann. Math. Statist.35 (1964)] have been introduced and studied in this paper for the purpose of testing mulitvariate independence. It is shown that the test statistics can be expressed as rank statistics which are easy to compute, have asymptotic normal distributions, and can detect mutual dependence in alternatives which are pairwise independent. The tests are compared to the Puri-Sen-Gokhale [[8]] tests and a normal theory test [ [1]] using Pitman efficiency.

Suggested Citation

  • Sinha, Bimal Kumar & Wieand, H. S., 1977. "Multivariate nonparametric tests for independence," Journal of Multivariate Analysis, Elsevier, vol. 7(4), pages 572-583, December.
    • Handle: RePEc:eee:jmvana:v:7:y:1977:i:4:p:572-583
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    Cited by:

    1. Khismatullina, Marina & Vogt, Michael, 2023. "Nonparametric comparison of epidemic time trends: The case of COVID-19," Journal of Econometrics, Elsevier, vol. 232(1), pages 87-108.
    2. Bakirov, Nail K. & Rizzo, Maria L. & Szekely, Gábor J., 2006. "A multivariate nonparametric test of independence," Journal of Multivariate Analysis, Elsevier, vol. 97(8), pages 1742-1756, September.

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