Estimation of Stress Strength Reliability of Inverse Weibull Distribution under Progressive First Failure Censoring

In this article, estimation of stress-strength reliability delta = P (Y < X) based on progressively first failure censored data from two independent inverse Weibull distributions with different shape and scale parameters is studied. Maximum likelihood estimator and asymptotic confidence interval of delta are obtained. Bayes estimator of delta under generalized entropy loss function using non-informative and gamma informative priors is derived. Also, highest posterior density credible interval of delta is constructed. Markov Chain Monte Carlo (MCMC) technique is used for Bayes computation. The performance of various estimation methods are compared by a Monte Carlo simulation study. Finally, a pair of real life data is analyzed to illustrate the proposed methods of estimation.