Median Double Ranked Set Sampling Method

Stratified Median Ranked Set Sampling: Optimum and Proportional Allocations

In this paper, for the Stratified Median Ranked Set Sampling (SMRSS), proposed by Ibrahim et al. (2010), we examine the proportional and optimum sample allocations that are two well-known methods for sample allocation in stratified sampling. We show that the variances of the mean estimators of a symmetric population in SMRSS using optimum and proportional allocations to strata are smaller than ...

Multistage Median Ranked Set Sampling for Estimating the Population Median

We modify RSS to come up with new sampling method, namely, Multistage Median Ranked Set Sampling (MMRSS). The MMRSS was suggested for estimating the population median and to increase the efficiency of the estimator for specific value of the sample size. The MMRSS was compared to the Simple Random Sampling (SRS), Ranked Set Sampling (RSS) and Median Ranked Set Sampling (MRSS) methods. It is foun...

Parametric Ranked Set Sampling*

Ranked set sampling was introduced by McIntyre (1952, Australian Journal of Agricultural Research, 3, 385-390) as a cost-effective method of selecting data if observations are much more cheaply ranked than measured. He proposed its use for estimating the population mean when the distribution of the data was unknown. In this paper, we examine the advantage, if any, that this method of sampling h...

Ranked Set Sampling

This paper is intended to provide the reader with an introduction to ranked set sampling, a statistical technique for data collection that generally leads to more efficient estimators than competitors based on simple random samples. Methods for obtaining ranked set samples are described and the structural differences between ranked set samples and simple random samples are discussed. Properties...

Ranked set sampling