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Independence tests based on the shape of the Standard Young Tableau

Author

Listed:
  • Jesús Enrique García

    (University of Campinas)

  • Verónica Andrea González-López

    (University of Campinas)

  • María Magdalena Kcala Álvaro

    (University of Campinas)

Abstract

We introduce a novel family of tests designed to assess the hypothesis of independence between two continuous random variables, X and Y. This test family is constructed around a new concept presented here-the shape vector derived from the Standard Young Tableau, obtained through the application of an algorithm [introduced by Schensted (Canad J Math 13:179–191, 1961. https://doi.org/10.4153/CJM-1961-015-3 )] to the permutation mapping the ranks of X observations onto the ranks of Y observations. We present diverse statistics based on the shape vector from the Standard Young Tableau. The empirical distributions associated with this innovative family of statistics are established through simulations, supported by various procedures detailed in this paper. The efficacy of dependence detection exhibited by this new test family is demonstrated through simulated scenarios and real datasets. Notably, the proposed family demonstrates a capability to detect dependence in situations where traditional tests of independence, such as those based on association or correlation coefficients, falter.

Suggested Citation

  • Jesús Enrique García & Verónica Andrea González-López & María Magdalena Kcala Álvaro, 2025. "Independence tests based on the shape of the Standard Young Tableau," Computational Statistics, Springer, vol. 40(9), pages 5043-5074, December.
    • Handle: RePEc:spr:compst:v:40:y:2025:i:9:d:10.1007_s00180-024-01597-9
    DOI: 10.1007/s00180-024-01597-9
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    References listed on IDEAS

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    1. Christian Genest & Bruno Rémillard, 2004. "Test of independence and randomness based on the empirical copula process," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 13(2), pages 335-369, December.
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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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