Inference for the Rayleigh Distribution Based on Progressive Type-II Fuzzy Censored Data

Pak, Abbas; Parham, Gholam Ali; Saraj, Mansour

doi:10.22237/jmasm/1398917880

Cited by 23 publications

(18 citation statements)

References 21 publications

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“…The initial values required for proceeding modified Newton-Raphson method chosen to be the symmetrical rank regression estimators. The comparisons between the parameter estimates were based on values from MSE where [8]: λ : is the estimate of λ respectively at the j th run. L: is the number of sample replicated chosen to be (500).…”

Section: Simulation Studymentioning

confidence: 99%

Bayesian Estimations with Fuzzy Data to Estimation Inverse Rayleigh Scale Parameter

Al-Sultany¹

2019

OJAppS

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In this paper, Bayesian computational method is used to estimate inverse Rayleigh Scale parameter with fuzzy data. Based on imprecision data, the Bayes estimates cannot be obtained in explicit form. Therefore, we provide Tierney and Kadane's approximation to compute the Bayes estimates of the scale parameter under Square error and Precautionary loss function using Non-informative Jefferys Prior. Also, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the scale parameter in terms of mean squared error values.

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Section: Simulation Studymentioning

confidence: 99%

Bayesian Estimations with Fuzzy Data to Estimation Inverse Rayleigh Scale Parameter

Al-Sultany¹

2019

OJAppS

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“…Some more details on fuzzy based Weibull distribution can be seen in References [29,30]. It is assumed that items are tested identically and simultaneously in each group.…”

Section: Design Of Proposed Planmentioning

confidence: 99%

Testing of Grouped Product for the Weibull Distribution Using Neutrosophic Statistics

Aslam

Arif

2018

Symmetry

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Parts manufacturers use sudden death testing to reduce the testing time of experiments. The sudden death testing plan in the literature can only be applied when all observations of failure time/parameters are crisp. In practice however, it is noted that not all measurements of continuous variables are precise. Therefore, the existing sudden death test plan can be applied if failure data/or parameters are imprecise, incomplete, and fuzzy. The classical statistics have the special case of neutrosophic statistics when there are no fuzzy observations/parameters. The neutrosophic fuzzy statistics can be applied for the testing of manufacturing parts when observations are imprecise, incomplete and fuzzy. In this paper, we will design an original neutrosophic fuzzy sudden death testing plan for the inspection/testing of the electronic product or parts manufacturing. We will assume that the lifetime of the product follows the neutrosophic fuzzy Weibull distribution. The neutrosophic fuzzy operating function will be given and used to determine the neutrosophic fuzzy plan parameters through a neutrosophic fuzzy optimization problem. The results of the proposed neutrosophic fuzzy death testing plan will be implemented with the aid of an example.

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“…First, for fixed θ = 1 and different choices of n and r, generated Type II censored samples were generated, say x = (x 1 ,…, x r ), from the exponential distribution using the method proposed by Aggarwala and Balakrishnan (1998). Each realization of x was fuzzified using the fuzzy information system (see Pak et al, 2014) …”

Section: Numerical Studymentioning

confidence: 99%

Estimating the Parameter of Exponential Distribution under Type II Censoring From Fuzzy Data

Makhdoom¹,

Nasiri²,

Pak³

2016

J. Mod. App. Stat. Meth.

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The problem of estimating the parameter of Exponential distribution on the basis of type II censoring scheme is considered when the available data are in the form of fuzzy numbers. The Bayes estimate of the unknown parameter is obtained by using the approximation forms of Lindley (1980) and Tierney and Kadane (1986) under the assumption of gamma prior. The highest posterior density (HPD) estimate of the parameter of interest is found. A Monte Carlo simulation is used to compare the performances of the different methods. A real data set is investigated to illustrate the applicability of the proposed methods.

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Inference for the Rayleigh Distribution Based on Progressive Type-II Fuzzy Censored Data

Cited by 23 publications

References 21 publications

Bayesian Estimations with Fuzzy Data to Estimation Inverse Rayleigh Scale Parameter

Bayesian Estimations with Fuzzy Data to Estimation Inverse Rayleigh Scale Parameter

Testing of Grouped Product for the Weibull Distribution Using Neutrosophic Statistics

Estimating the Parameter of Exponential Distribution under Type II Censoring From Fuzzy Data

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