Symmetric and Asymmetric Bayesian Estimation For Lindley Distribution Based on Progressive First Failure Censored Data

El-Din, M. M. Mohie; Amein, M. M.; El-Attar, H. E.; Hussam, Eslam

doi:10.18576/msl/060306

Cited by 10 publications

(7 citation statements)

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“…In this section, some results are represented depending on Monte-Carlo simulation, for comparing the estimates of (R) performance using MLE and MOM estimators fundamentally for many sample sizes. e following sample sizes are considered; (n, m) � (5, 5), (10,10), (20, 20), (30, 30), (40, 40), (50, 50), and (100, 100). From each sample, the estimates are computed for the parameters using MLE and method of moment estimation.…”

Section: Simulation Studymentioning

confidence: 99%

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Estimate Stress‐Strength Reliability Model Using Rayleigh and Half‐Normal Distribution

Alamri

El‐Raouf

Ismail

et al. 2021

Computational Intelligence and Neuroscience

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In the field of life testing, it is very important to study the reliability of any component under testing. One of the most important subjects is the “stress-strength reliability” term which always refers to the quantity P X > Y in any statistical literature. It resamples a system with random strength (X) that is subjected to a random strength (Y) such that a system fails in case the stress exceeds the strength. In this study, we consider stress-strength reliability where the strength (X) follows Rayleigh-half-normal distribution and stress ( Y 1 , Y 2 , Y 3 , and Y 4 ) follows Rayleigh-half-normal distribution, exponential distribution, Rayleigh distribution, and half-normal distribution, respectively. This effort comprises determining the general formulations of the reliabilities of a system. Also, the maximum likelihood estimation approach and method of moment (MOM) will be utilized to estimate the parameters. Finally, reliability has been attained utilizing various values of stress and strength parameters.

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Section: Simulation Studymentioning

confidence: 99%

“…e estimation of R � P(Y < X) is studied by AI-Hussaini [9] based on a finite mixture of lognormal components. For more reading, see [10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Estimate Stress‐Strength Reliability Model Using Rayleigh and Half‐Normal Distribution

Alamri

El‐Raouf

Ismail

et al. 2021

Computational Intelligence and Neuroscience

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“…step-stress (see, e.g., [1]). Two other common types are constant stress, where the test is conducted under a constant degree of stress for the entire experiment, and progressive stress, where all test units are subjected to stress as a function of time, and the stress increases on the experimented items as the time of the experiment increases (see El-Din et al [2,3] for more details about acceleration and its models).…”

Section: Introductionmentioning

confidence: 99%

“…Then, after this time, the stress load is increased by a fixed value for a certain period and so on until all the units have failed or the experiment ends. One of the most common methods of simple step-stress ALT has two levels (see, e.g., El-Din et al [2][3][4].) Two types of censoring approaches can be applied to units: Type I censoring and Type II censoring.…”

Section: Introductionmentioning

confidence: 99%

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Study on Lindley Distribution Accelerated Life Tests: Application and Numerical Simulation

Hussam¹,

Riad

Mubarak

et al. 2020

Symmetry

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Saving money and time are very important in any research project, so we must find a way to decrease the time of the experiment. This method is called the accelerated life tests (ALT) under censored samples, which is a very efficient method to reduce time, which leads to a decrease in the cost of the experiment. This research project includes inference on Lindley distribution in a simple step-stress ALT for the Type II progressive censored sample. The paper contains two major sections, which are a simulation study and a real-data application on the experimental design of an industry experiment on lamps. These sections are used to conduct results on the study of the distribution. The simulation was done using Mathematica 11 program. To use real data in the censored sample, we fitted them to be compatible with the Lindley distribution using the modified Kolmogorov–Smirnov (KS) goodness of fit test for progressive Type II censored data. We used the tampered random variable (TRV) acceleration model to generate early failures of items under stress. We also found the values of the distribution parameter and the accelerating factor using the maximum likelihood estimation of (MLEs) and Bayes estimates (BEs) using symmetric loss function for both simulated data and real data. Next, we estimated the upper and lower bounds of the parameters using three methods, namely approximate confidence intervals (CIs), Bootstrap CIs, and credible CIs, for both parameters of the distribution, ψ and ζ. Finally, we found the value of the parameter for the real data set under normal use conditions and stress conditions and graphed the reliability functions under normal and accelerated use.

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Inference on adaptive Type-II progressive hybrid censoring under partially accelerated life test for Gompertz distribution

Alam,

Anwar,

Sharma

2023

Int J Syst Assur Eng Manag

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Symmetric and Asymmetric Bayesian Estimation For Lindley Distribution Based on Progressive First Failure Censored Data

Cited by 10 publications

References 0 publications

Estimate Stress‐Strength Reliability Model Using Rayleigh and Half‐Normal Distribution

Estimate Stress‐Strength Reliability Model Using Rayleigh and Half‐Normal Distribution

Study on Lindley Distribution Accelerated Life Tests: Application and Numerical Simulation

Inference on adaptive Type-II progressive hybrid censoring under partially accelerated life test for Gompertz distribution

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