Estimation of System Reliability Based on Moving Extreme and MiniMax Ranked Set Sampling for Exponential Distributions

In this article, we consider the maximum likelihood estimation (MLE) of the system reliability for the exponential distribution. We propose the estimation of the system reliability based on moving extreme and MiniMax ranked set sampling mechanisms. Since the proposed MLE estimators of cannot be obtained in a closed form, we apply Mehrotra and Nanda’s modified MLE methodology. The performance of the suggested estimators is compared with their competitors based on simple random sample by Monte Carlo simulations under both perfect and imperfect ranking assumptions. Real data from the medical field is analyzed to show the applicability of the proposed estimators.