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Contingency tables with fuzzy information

Author

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  • S. M. Taheri
  • G. Hesamian
  • R. Viertl

Abstract

This paper extends the classical methods of analysis of a two-way contingency table to the fuzzy environment for two cases: (1) when the available sample of observations is reported as imprecise data, and (2) the case in which we prefer to categorize the variables based on linguistic terms rather than as crisp quantities. For this purpose, the α-cuts approach is used to extend the usual concepts of the test statistic and p-value to the fuzzy test statistic and fuzzy p-value. In addition, some measures of association are extended to the fuzzy version in order to evaluate the dependence in such contingency tables. Some practical examples are provided to explain the applicability of the proposed methods in real-world problems.

Suggested Citation

  • S. M. Taheri & G. Hesamian & R. Viertl, 2016. "Contingency tables with fuzzy information," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(20), pages 5906-5917, October.
    • Handle: RePEc:taf:lstaxx:v:45:y:2016:i:20:p:5906-5917
    DOI: 10.1080/03610926.2014.953688
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    Cited by:

    1. Carmen Nadia Ciocoiu & Adina Liliana Prioteasa & Sofia Elena Colesca, 2020. "Risk Management Implementation for Sustainable Development of Romanian SMEs: A Fuzzy Approach ...........," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 22(55), pages 726-726, August.

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