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Dependency measure for sets of random events or random variables

Author

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  • Stoyanov, Jordan

Abstract

For sets of random events or variables ranging from mutual independence to total dependence we introduce a dependency measure based on a more detailed definition of the independency property. The separating property of that measure allows to order sets of random elements as "more" or as "less" dependent. Related topics are also discussed.

Suggested Citation

  • Stoyanov, Jordan, 1995. "Dependency measure for sets of random events or random variables," Statistics & Probability Letters, Elsevier, vol. 23(1), pages 13-20, April.
    • Handle: RePEc:eee:stapro:v:23:y:1995:i:1:p:13-20
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    References listed on IDEAS

    as
    1. George Kimeldorf & Allan Sampson, 1989. "A framework for positive dependence," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 41(1), pages 31-45, March.
    2. Nelsen, Roger B., 1992. "On measures of association as measures of positive dependence," Statistics & Probability Letters, Elsevier, vol. 14(4), pages 269-274, July.
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    Cited by:

    1. Balek, Vladimír & Mizera, Ivan, 1997. "On the logical independence of the identities defining the stochastic independence of random events," Statistics & Probability Letters, Elsevier, vol. 31(4), pages 281-284, February.
    2. Ostrovska, Sofiya, 2001. "Sets of random variables with a given uncorrelation structure," Statistics & Probability Letters, Elsevier, vol. 55(4), pages 359-366, December.

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