In this paper we have adopted the Khoshnevisan et al. (2007) family of estimators to extreme
ranked set sampling (ERSS) using information on single and two auxiliary variables. Expressions
for mean square error (MSE) of proposed estimators are derived to first order of approximation.
Monte Carlo simulations and real data sets have been used to illustrate the method. The results
indicate that the estimators under ERSS are more efficient as compared to estimators based on
simple random sampling (SRS), when the underlying populations are symmetric.Peer Reviewe
