Abstract.
In this paper a new approach is presented for testing statistical hypotheses when the hypotheses are fuzzy rather than crisp.
In order to establish optimality criteria, we first give new definitions for probability of type I and type II errors. Then, we state and prove the Neyman-Pearson Lemma, on the basis of these new errors, for testing fuzzy hypotheses, and we give a few examples.
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Received February 1998
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Taheri, S., Behboodian, J. Neyman-Pearson Lemma for fuzzy hypotheses testing. Metrika 49, 3–17 (1999). https://doi.org/10.1007/s001840050021
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DOI: https://doi.org/10.1007/s001840050021