Inference for reliability in a multicomponent stress-strength model from generalized inverted exponential lifetime distribution under progressive first failure censoring

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This article considers the non-Bayesian and Bayesian estimation procedures for multicomponent stress-strength reliability (MSSR) from generalized inverted exponential lifetime distributions using a progressively first failure censoring scheme. For the non-Bayesian estimation method of MSSR, the maximum likelihood estimation method is used, and for the Bayesian estimation method, the Metropolis-Hastings algorithm is taken into account. Also, the highest posterior density credible interval and the asymptotic confidence interval for MSSR in the case of Bayesian and non-Bayesian estimation methods, respectively, are obtained. A Monte Carlo numerical study is conducted to compare different types of estimates. For illustrative purposes, a real data analysis is carried out.