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Testing statistical hypotheses for intuitionistic fuzzy data

  • Methodologies and Application
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Abstract

The present work is aimed to extend the classical statistical methods based on intuitionistic fuzzy data to hypothesis test about exact parameter of the underlying population. In this approach, the concepts of the intuitionistic fuzzy type-I error, intuitionistic fuzzy type-II error, intuitionistic fuzzy power and intuitionistic fuzzy p value are extended at a given significance level. A degree-based criterion is also suggested to compare the intuitionistic fuzzy p value and a specific significance level to make decision on whether accepting or rejecting the null hypothesis. An applied example is examined based on the proposed method in both parametric and nonparametric cases. The results indicate that the proposed method can be successfully applied for all parametric/nonparametric statistical hypotheses testing based on intuitionistic fuzzy continuous data.

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Acknowledgements

The authors would like to thank the editor and anonymous reviewer for her/his 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

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

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Akbari, M.G., Hesamian, G. Testing statistical hypotheses for intuitionistic fuzzy data. Soft Comput 23, 10385–10392 (2019). https://doi.org/10.1007/s00500-018-3590-2

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