Data driven rank tests for independence

W.C.M. Kallenberg, Teresa Ledwina

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    We introduce new rank tests for testing independence. The new testing procedures are sensitive not only for grade linear correlation, but also for grade correlations of higher-order polynomials. The number of polynomials involved is determined by the data. Model selection is combined with application of the score test in the selected model. Whereas well-known tests as Spearman's test or Hoeffding's test may completely break down for alternatives that are dependent but have low grade linear correlation, the new tests have greater power stability. Monte Carlo results clearly show this behavior. Theoretical support is obtained by proving consistency of the new tests.
    Original languageUndefined
    Pages (from-to)285-301
    Number of pages17
    JournalJournal of the American Statistical Association
    Issue number445
    Publication statusPublished - 1999


    • Monte Carlo study
    • Copula
    • Correlation
    • Rank test
    • Independence
    • IR-62350
    • Consistency
    • Model selection
    • EWI-12854

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