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Testing exponentiality for imprecise data and its application

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Abstract

The goodness-of-fit test for a given data set is an important problem in statistical inference and its applications. In this paper, we consider this problem for the exponential distribution which is widely used in the various areas under fuzzy environment. To this end, we need an approach that the most commonly used tests in statistics such as Kolmogorov–Smirnov and Anderson–Darling are made usable for fuzzy data set. For this purpose, we use the \(\alpha \)-pessimistic technique and Monte Carlo simulation method.

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Acknowledgements

The authors thank the Associate Editor and anonymous referees for making some valuable suggestions which led to a considerable improvement in the presentation of this manuscript.

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Authors and Affiliations

  1. Department of Statistics, Faculty of Mathematics and Statistics, University of Birjand, Birjand, Iran

    J. Zendehdel, M. Rezaei, M. G. Akbari & H. Alizadeh Noughabi

  2. Department of Statistics, Faculty of Mathematical Sciences, University of Guilan, Guilan, Iran

    R. Zarei

Authors
  1. J. Zendehdel
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  2. M. Rezaei
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  3. M. G. Akbari
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  4. R. Zarei
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  5. H. Alizadeh Noughabi
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Corresponding author

Correspondence to M. G. Akbari.

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The authors declare no (financial or non-financial) potential conflicts of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by V. Loia.

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Zendehdel, J., Rezaei, M., Akbari, M.G. et al. Testing exponentiality for imprecise data and its application. Soft Comput 22, 3301–3312 (2018). https://doi.org/10.1007/s00500-017-2566-y

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  • DOI: https://doi.org/10.1007/s00500-017-2566-y

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