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INFERENTIAL ANALYSIS OF THE RE-MODELED STRESS-STRENGTH SYSTEM RELIABILITYWITH APPLICATION TO THE REAL DATAKeywords: Stress-Strength model , maximum likelihood estimate , Bayes estimate , empirical distribution function , Gibbs sampler , Metropolis-Hastings algorithm , highest posterior density credible interval. Abstract: The present study deals with the classical and Bayesian analysis of re-modeledstress-strength system reliability by considering Weibull distribution as the distribution of boththe stress and strength variables. The proposed re-modeled stress-strength system reliability isdefined as the probability that the system is capable to withstand the maximum operated stress atits minimum strength i.e., P[U>V], where U=Min(X1, X2…Xm) and V=Max(Y1,Y2,……Yn). Theobservations X1, X2…Xm and Y1,Y2,……Yn are the measurements on the strength and stressvariables at different time epochs. The goodness-of-fit of the two real data sets for the proposedmodel is also demonstrated.
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