Interval estimation of multicomponent stress-strength reliability based on inverse Weibull distribution

This paper considers interval estimation of stress-strength reliability of k-out-of-n system when the stress and strength components follow inverse Weibull distributions. Besides the asymptotic and bootstrap confidence intervals, we derive HPD credible intervals when the shape parameter is known or unknown. We also propose the pivotal quantity and generalized confidence interval of reliability. We study the estimation of multicomponent stress-strength reliability using lower record values. Generalized, asymptotic, and bootstrap confidence intervals are derived using lower record values. We also derive confidence intervals of multicomponent stress-strength reliability assuming the shape parameters are different. We propose HPD credible intervals, generalized and bootstrap confidence intervals. Monte Carlo simulation is performed to compare the confidence intervals. Real data examples are presented to demonstrate the practicability of the confidence intervals. (C) 2021 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.

Automated summary

This study considers interval estimation of stress-strength reliability using inverse Weibull distributions for stress and strength components. HPD credible intervals, generalized confidence intervals, and bootstrap confidence intervals are proposed for different shape parameter scenarios. Monte Carlo simulations and real data examples demonstrate the practicality of these methods.