Abstract
A stress-strength reliability model compares the strength and stresses on a certain system; it is used not only primarily in reliability engineering and quality control but also in economics, psychology, and medicine. In this paper, a novel extension of stress-strength models is presented. The mew model is applied under the generalized exponential distribution. The maximum likelihood estimator, asymptotic distribution, and Bayesian estimation are obtained. A comprehensive simulation study along with real data analysis is performed for illustrating the importance of the new stress-strength model.
Highlights
Stress-strength reliability analysis is a statistical analysis of the interference of of the strength of the component and the stresses placed on the component. e stress-strength reliability analysis is a statistical tool used in reliability engineering.In a stress-strength reliability model, both strength and stresses are considered as separate random variables
In this work, we study the conditional stressstrength model for two-parameter generalized exponential (GE) distributed components, and the Bayesian estimation is considered. e GE distribution can be used as an alternative to gamma, Weibull, and log-normal distributions
We derive the maximum likelihood estimation (MLE) of the R|a,b model; and the asymptotic distribution of those is presented in order to constructing the corresponding confidence interval
Summary
Stress-strength reliability analysis is a statistical analysis of the interference of of the strength of the component and the stresses placed on the component. e stress-strength reliability analysis is a statistical tool used in reliability engineering. Rezaei et al [3] presented a list of probability distributions used under the stress-strength reliability model. Rasekhi et al [4] presented a Bayesian and the classical inference of reliability in multicomponent stress-strength under the generalized logistic model. We suppose that we know these two components have been worked till a known time, and we are going to have some inferences on R For this case, Saber and Khorshidian [6] introduce the conditional stress-strength model R|a,b: R|a,b P(X > Y|X > a, Y > b). Saber and Khorshidian [6] studied this model for the case of exponential distributed components under the nonparametric case, and the Bayesian estimation is ignored. In this work, we study the conditional stressstrength model for two-parameter generalized exponential (GE) distributed components, and the Bayesian estimation is considered. A simulation study is presented in Section 4, and Section 5 has been devoted to applying a real dataset to the recommended model
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