الفهرس 
On Estimation of stress-strength parameter based on progressive censoring in some reliability models
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Abstract
In this thesis, the estimation of stress-strength parameter R = P(Y < X), when X and Y are independent random variables those follow the samere- liability model under progressive censoring of type II is studied. Among many important models in reliability, we propose the estimation of R for Weibull, Burr Type XII and Rayleigh distributions. Di{uFB00}erent meth- ods of estimation are utilized as maximum likelihood estimator (MLE), uniformly minimum variance unbiased estimator (UMVUE) and Bayes estimator. Bayes estimation is obtained by using the squared error loss function in case of conjugate and non-informative priors for the parame- ters of models. Also, we obtained the exact con{uFB01}dence interval based on the MLE estimator. Simulation is used for the purpose of illustration and comparing the di{uFB00}erent estimators using the mean square error (MSE), also we give some real data examples