Chance Hypotheses Testing

S. Sampath and L. Pephine Renitta
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S. Sampath: University of Madras, Chepauk, India
L. Pephine Renitta: University of Madras, Chepauk, India

International Journal of Fuzzy System Applications (IJFSA), 2016, vol. 5, issue 3, 77-108

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.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jfsa00:v:5:y:2016:i:3:p:77-108

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