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On dominations between measures of dependence

Author

Listed:
  • Bradley, Richard C.
  • Bryc, Wlodzimierz
  • Janson, Svante

Abstract

Suppose one has two measures of dependence between two or more families of random variables. One of the measures is said to "dominate" the other if the latter becomes arbitrarily small as the former becomes sufficiently small. A description is given of the entire pattern of dominations between arbitrary pairs of measures of dependence that are based on the usual norms of the bilinear form "covariance". Also, for a broader class of measures of dependence, some carlier "domination inequalities" are shown to be essentially sharp.

Suggested Citation

  • Bradley, Richard C. & Bryc, Wlodzimierz & Janson, Svante, 1987. "On dominations between measures of dependence," Journal of Multivariate Analysis, Elsevier, vol. 23(2), pages 312-329, December.
    • Handle: RePEc:eee:jmvana:v:23:y:1987:i:2:p:312-329
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    Citations

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    Cited by:

    1. Aiting Shen & Siyao Zhang, 2021. "On Complete Consistency for the Estimator of Nonparametric Regression Model Based on Asymptotically Almost Negatively Associated Errors," Methodology and Computing in Applied Probability, Springer, vol. 23(4), pages 1285-1307, December.
    2. Bradley, Richard C., 1996. "A covariance inequality under a two-part dependence assumption," Statistics & Probability Letters, Elsevier, vol. 30(4), pages 287-293, November.
    3. Abberger, Klaus, 1994. "Nichtparametrische Schätzung bedingter Quantile in Finanzmarktdaten," Discussion Papers, Series II 225, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".

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