Importance sampling is a classical Monte Carlo technique in which a random sample from one probability density, π1, is used to estimate an expectation with respect to another, π. The importance sampling estimator is strongly consistent and, as long as two simple moment conditions are satisfied, it obeys a central limit theorem (CLT). Moreover, there is a simple consistent estimator for the asym...

Double robust extreme ranked set sampling (DRERSS) and its properties for estimating the population median are suggested. The performance of DRERSS with respect to simple random sampling (SRS), ranked set sampling (RSS) and extreme ranked set sampling (ERSS) schemes is considered. Real data set that consist of heights of 346 students are used to evaluate the DRERSS method. It is found that when...

In sampling theory, a wide variety of techniques is used to obtain efficient estimators for the population mean. The commonly used method to obtain the estimator for population mean is simple random sampling without replacement (SRSWOR) when there is no auxiliary variable available. There are methods that use the auxiliary information of the study characteristics. If there exists an auxiliary v...