Comparison of two sampling schemes in estimating the stress-strength reliability under the proportional reversed hazard rate model

Abstract

In this paper, point and interval estimation of stress-strength reliability based on lower record ranked set sampling scheme under the proportional reversed hazard rate model are considered. Maximum likelihood, uniformly minimum variance unbiased, and Bayesian estimators of $\mathcal{R}$ are derived and their performances are compared. Various confidence intervals for the parameter $\mathcal{R}$ are constructed, and compared based on the simulation study. Moreover, the record ranked set sampling scheme is compared with ordinary records in case of interval estimations. Finally, a data set has been analyzed for illustrative purposes.

Multicomponent Stress-strength Reliability with Exponentiated Teissier Distribution

“…Thereafter, the problem of estimating R has been discussed by a great number of researchers. Of the recent efforts pertaining to stress-strength models, to name a few, are Al-Mutairi, Ghitany, and Kundu (2013), Genc (2013), Singh, Singh, and Sharma (2014), Rezaei, Noughabi, and Nadarajah (2015), Akgül and Şenoglu (2017), Mahdizadeh and Zamanzade (2018), Abravesh, Ganji, and Mostafaiy (2019), Jose and Drisya (2020), Sadeghpour, Nezakati, and Salehi (2021) and Biswas, Chakraborty, and Mukherjee (2021).…”