You are in:Home/Publications/Estimation of Stress-Strength Reliability for Quasi Lindely Distribution

Ass. Lect. Shaimaa Hamed Abd Allah Elmaghawry Mohamed Ramdan :: Publications:

Title:
Estimation of Stress-Strength Reliability for Quasi Lindely Distribution
Authors: M.M. Mohie El-Din, A. Sadek, Shaimaa H. Elmeghawry
Year: 2018
Keywords: Quasi Lindley distribution; Stress-strength reliability; Maximum likelihood estimation; Asymptotic confidence interval; Bayesian estimation; Importance sampling technique; MCMC technique via Metropolis-Hastings algorithm
Journal: The Journal of Advances in Systems Science and Applications (ASSA).
Volume: Not Available
Issue: Not Available
Pages: 1–12
Publisher: Not Available
Local/International: International
Paper Link: Not Available
Full paper Not Available
Supplementary materials Not Available
Abstract:

This paper discussed the problem of estimating of the stress-strength reliability R = P r(Y < X). It is assumed that the strength of a system X, and the environmental stress applied on it Y, follow the Quasi Lindley Distribution(QLD). Stress-strength reliability is studied using the maximum likelihood, and Bayes estimations. Asymptotic confidence interval for reliability is obtained. Bayesian estimations were proposed using two different methods: Importance Sampling technique, and MCMC technique via Metropolis-Hastings algorithm, under symmetric loss function (squared error) and asymmetric loss functions (linex, general entropy). The behaviors of the maximum likelihood and Bayes estimators of stress-strength reliability have been studied through the Monte Carlo simulation study.

Google ScholarAcdemia.eduResearch GateLinkedinFacebookTwitterGoogle PlusYoutubeWordpressInstagramMendeleyZoteroEvernoteORCIDScopus