ESTIMATION OF THE POPULATION MEDIAN OF SYMMETRIC AND ASYMMETRIC DISTRIBUTIONS USING DOUBLE ROBUST EXTREME RANKED SET SAMPLING

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 the underlying distribution is symmetric, the DRERSS estimators are unbiased of the population median. When the sample size is odd, DRERSS is efficient than SRS, ERSS, and RSS. When the sample size is even, DRERSS is more efficient than RSS and ERSS if the underlying distribution is symmetric, and for asymmetric distributions, DRERSS is more efficient than RSS and ERSS for based on the same number of measured units.