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Neyman–Pearson lemma based on intuitionistic fuzzy parameters

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Abstract

The present work aims to extend the classical Neyman–Pearson lemma based on a random sample of exact observations to test intuitionistic fuzzy hypotheses. In this approach, we extend the concepts of type-I error, type-II and power of test. Some applied examples are provided to illustrate the proposed method. In addition, the proposed method is examined to be compared with an existing method.

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Acknowledgements

The authors would like to thank the editor and anonymous reviewer for his/her constructive suggestions and comments, which improved the presentation of this work.

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Authors and Affiliations

  1. Department of Statistics, University of Birjand, Birjand, 615-97175, Iran

    Mohammad Ghasem Akbari

  2. Department of Statistics, Payame Noor University, Tehran, 19395-3697, Iran

    Gholamreza Hesamian

Authors
  1. Mohammad Ghasem Akbari
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  2. Gholamreza Hesamian
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Correspondence to Gholamreza Hesamian.

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Akbari, M.G., Hesamian, G. Neyman–Pearson lemma based on intuitionistic fuzzy parameters. Soft Comput 23, 5905–5911 (2019). https://doi.org/10.1007/s00500-018-3252-4

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