Estimation of Stress-Strength Reliability Based on Ranked Set Sampling for Generalized Exponential Distribution

In this paper, we consider the estimation of the reliability in a stress-strength model by the maximum likelihood and Bayesian methods under generalized exponential distribution. We provide the estimation of the reliability with simple random sampling and ranked set sampling methods. Lindley's algorithm is used to obtain the approximate Bayesian estimation of the reliability with gamma priors. The results are compared in terms of relative efficiency in different sample sizes through a simulation study with R-software. Finally, two real data examples are presented to estimate reliability.