Stress-strength reliability estimation of multicomponent system with non-identical strength components from inverse Pareto distribution

In the case of multicomponent stress strength reliability, independent and identical components are often used. Still, the assumption of identical components may not be always true in real life due to the structure of the system. In this article, the reliability of an s-out-of-k system in the case of non-identical strength components, and a common stress component is estimated. The non-identical strength component and common stress components follow inverse Pareto distribution. To estimate the multicomponent stress-strength reliability both classical and Bayesian paradigms are used. The maximum likelihood estimates and Bayes estimates are obtained as point estimates and asymptotic confidence interval and highest posterior density credible intervals are obtained as interval estimates under the classical and Bayesian paradigms, respectively. The Bayes estimates are obtained using the Markov chain Monte Carlo technique. Different estimates obtained in the study are compared using the Monte Carlo simulation study. For illustrative purposes, a real data set is also analyzed.