Estimation of stress–strength reliability for inverse exponentiated distributions with application

Abstract

PurposeInferences for multicomponent reliability is derived for a family of inverted exponentiated densities having common scale and different shape parameters.Design/methodology/approachDifferent estimates for multicomponent reliability is derived from frequentist viewpoint. Two bootstrap confidence intervals of this parametric function are also constructed.FindingsForm a Monte-Carlo simulation study, the authors find that estimates obtained from maximum product spacing and Right-tail Anderson–Darling procedures provide better point and interval estimates of the reliability. Also the maximum likelihood estimate competes good with these estimates.Originality/valueIn literature several distributions are introduced and studied in lifetime analysis. Among others, exponentiated distributions have found wide applications in such studies. In this regard the authors obtain various frequentist estimates for the multicomponent reliability by considering inverted exponentiated distributions.

Fuzzy stress and strength reliability based on the generalized mixture exponential distribution

“…Yazgan et al (2022) [7] considered the estimation of stress-strength reliability in the presence of fuzziness when the two random variables follow the WE distribution. Kumari et al (2023) [8] studied the stress-strength reliability for inverse exponentiated distributions.…”