Testing exponentiality for imprecise data and its application

Zendehdel, Javad; Rezaei, Mehran; Akbari, Mohammad Ghasem; Zarei, Reza; Noughabi, Hadi Alizadeh

doi:10.1007/s00500-017-2566-y

Cited by 3 publications

(1 citation statement)

References 21 publications

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“…Through a Monte Carlo simulation, they computed the power values of the tests under 20 alternatives. Similarly, Zendehdel et al (2018) introduced some exponentiality tests for fuzzy data. between lifetime distributions because CRKL is more sensitive to earlier difference.…”

Section: Test Based On Entropy For Fuzzy Datamentioning

confidence: 99%

An Updated Review of Goodness of Fit Tests Based on Entropy

Noughabi

Borzadaran

2020

JIRSS

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Different approaches to goodness of fit (GOF) testing are proposed. This survey intends to present the developments on Goodness of Fit based on entropy during the last 50 years, from the very first origins until the most recent advances for different data and models. Goodness of fit tests based on Shannon entropy was started by Vasicek in 1976 and were continued by many authors. In this paper, we describe different GOF tests constructed by authors from the beginning to now. First, the problem of GOF and different types of GOF are stated. Then, the method of GOF tests based on entropy for complete and censored data is explained and all works proposed by authors in this subject are mentioned.

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Section: Test Based On Entropy For Fuzzy Datamentioning

confidence: 99%

An Updated Review of Goodness of Fit Tests Based on Entropy

Noughabi

Borzadaran

2020

JIRSS

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Maximum entropy based testing for fuzzy exponential random variable and its applications

Zendehdel,

Zarei,

Akbari

2024

Comp. Appl. Math.

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A test for fuzzy exponentiality based on Kullback-Leibler information

Kong

2022

IFS

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The exponential distribution has been widely used in engineering, social and biological sciences. In this paper, we propose a new goodness-of-fit test for fuzzy exponentiality using α-pessimistic value. The test statistics is established based on Kullback-Leibler information. By using Monte Carlo method, we obtain the empirical critical points of the test statistic at four different significant levels. To evaluate the performance of the proposed test, we compare it with four commonly used tests through some simulations. Experimental studies show that the proposed test has higher power than other tests in most cases. In particular, for the uniform and linear failure rate alternatives, our method has the best performance. A real data example is investigated to show the application of our test.

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Testing exponentiality for imprecise data and its application

Cited by 3 publications

References 21 publications

An Updated Review of Goodness of Fit Tests Based on Entropy

An Updated Review of Goodness of Fit Tests Based on Entropy

Maximum entropy based testing for fuzzy exponential random variable and its applications

A test for fuzzy exponentiality based on Kullback-Leibler information

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