Stress-strength reliability of Weibull distribution based on progressively censored samples

Based on progressively Type-II censored samples, this paper deals with inference for the stress-strength reliability R = P(Y < X) when X and Y are two independent Weibull distributions with different scale parameters, but having the same shape parameter. The maximum likelihood estimator, and the approximate maximum likelihood estimator of R are obtained. Different confidence intervals are presented. The Bayes estimator of R and the corresponding credible interval using the Gibbs sampling technique are also proposed. Further, we consider the estimation of R when the same shape parameter is known. The results for exponential and Rayleigh distributions can be obtained as special cases with different scale parameters. Analysis of a real data set as well a Monte Carlo simulation have been presented for illustrative purposes.

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