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On estimation of R=P(Y<X) for exponential distribution under progressive type-II censoring
Journal of Statistical Computation and Simulation Cilt 82 ss. 729-744
Scopus Toplam 117 atıf DOI
This paper deals with the estimation of the stress-strength parameter R=P(Y<X), when X and Y are independent exponential random variables, and the data obtained from both distributions are progressively type-II censored. The uniformly minimum variance unbiased estimator and the maximum-likelihood estimator (MLE) are obtained for the stress-strength parameter. Based on the exact distribution of the MLE of R, an exact confidence interval of R has been obtained. Bayes estimate of R and the associated credible interval are also obtained under the assumption of independent inverse gamma priors. An extensive computer simulation is used to compare the performances of the proposed estimators. One data analysis has been performed for illustrative purpose. © 2012 Taylor and Francis Group, LLC.
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Atıf Yapan Yayın
Estimation of stress-strength reliability for generalized Gompertz distribution under progressive type-II censoring
Hacettepe Journal of Mathematics and Statistics Cilt 52 ss. 1379-1395
Scopus Havuzumuzda Open Access 7 atıf almış
In this study, the stress-strength reliability, R = P (Y < X) where Y represents the stress of a component and X represents this component’s strength, is obtained when X and Y have two independents generalized Gompertz distribution with different shape parameters under progressive type-II censoring. The Bayes and maximum likelihood estimators of stress-strength reliability can not be acquired in closed forms. The approximate Bayes estimators under squared error loss function by using Lindley’s approximations for stressstrength reliability are derived. A Monte Carlo simulation study is done to check performances of the approximate Bayes against performances of maximum likelihood estimators and observe the coverage probabilities and the intervals’ average width. In addition, the coverage probabilities of the parametric bootstrap estimates are calculated. Two applications based on real datasets are provided.
Atıf Yapan Makale Bilgileri
Kurumlar (3)
PTT Chief Directorate Konya, Turkey
Selçuk Tip Fakültesi Konya, Turkey
Selçuk Üniversitesi Selçuklu, Turkey