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Chance Hypotheses Testing

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  • S. Sampath

    (University of Madras, Chepauk, India)

  • L. Pephine Renitta

    (University of Madras, Chepauk, India)

Abstract

This paper considers the problem of testing hypotheses about hybrid distributions which are models representing situations where impreciseness (explained through fuzzy measure) and randomness (explained through probability measure) coexist. A criterion similar to the Neyman-Pearson criterion is proposed for testing a simple chance null hypothesis against a simple chance alternative hypothesis. The suggested criterion has been applied for testing hypotheses about hybrid triangular Bernoulli distribution and hybrid Poisson distribution. Optimal properties of the resulting tests have also been investigated.

Suggested Citation

  • S. Sampath & L. Pephine Renitta, 2016. "Chance Hypotheses Testing," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 5(3), pages 77-108, July.
    • Handle: RePEc:igg:jfsa00:v:5:y:2016:i:3:p:77-108
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