Testing exponentiality for imprecise data and its application

  • J. Zendehdel
  • M. Rezaei
  • M. G. Akbari
  • R. Zarei
  • H. Alizadeh Noughabi
Methodologies and Application
  • 28 Downloads

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.

Keywords

Goodness-of-fit test Exponential distribution Fuzzy data set \(\alpha \)-Pessimistic Monte Carlo simulation 

Notes

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.

Compliance with ethical standards

Conflict of interest

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

Human and animal rights

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

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • J. Zendehdel
    • 1
  • M. Rezaei
    • 1
  • M. G. Akbari
    • 1
  • R. Zarei
    • 2
  • H. Alizadeh Noughabi
    • 1
  1. 1.Department of Statistics, Faculty of Mathematics and StatisticsUniversity of BirjandBirjandIran
  2. 2.Department of Statistics, Faculty of Mathematical SciencesUniversity of GuilanGuilanIran

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