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H. Torabi, J. Behboodian and S. M. Taheri, “Neyman- Pearson Lemma for Fuzzy Hypotheses Testing withVague Data,” Metrika, Vol. 64, No. 3, 2006, pp. 289-304. doi:10.1007/s00184-006-0049-8

has been cited by the following article:

• TITLE: Sequential Test of Fuzzy Hypotheses

  AUTHORS: Mohammad Ghasem Akbari

  KEYWORDS: Canonical Fuzzy Number, Fuzzy Hypotheses, Type I and II Error Sizes, Sequential Probability Ratio Test

  JOURNAL NAME: Open Journal of Statistics, Vol.1 No.2, August 1, 2011

  ABSTRACT: In testing statistical hypotheses, as in other statistical problems, we may be confronted with fuzzy concepts. This paper deals with the problem of testing hypotheses, when the hypotheses are fuzzy and the data are crisp. We first give new definitions for notion of mass (density) probability function with fuzzy parameter, probability of type I and type II errors and then state and prove the sequential probability ratio test, on the basis of these new errors, for testing fuzzy hypotheses. Numerical examples are also provided to illustrate the approach.