Double Median Ranked Set Sample: Comparing To Other Double Ranked Samples For Mean And Ratio Estimators

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 ...

Unbiased Ratio Estimators of the Mean in Stratified Ranked Set Sampling

Stratified ranked set sampling (StRSS) combines the advantages of stratification and ranked set sampling (RSS). In this paper, we propose several unbiased ratio type estimators using StRSS, when population mean of the auxiliary variable is known. The variances of the proposed unbiased ratio-type estimators are obtained to first degree of approximation. In simulation study the proposed estimator...

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...

Extreme ranked set sampling: A comparison with regression and ranked set sampling estimators

Ranked set sampling (RSS) assumed perfect ranking i.e. there will be no errors in ranking the units with respect to the variable of interest. In fact for most practical applications, it is not easy to rank the units without errors in ranking. There will be a loss in efficiency, i.e. RSS will give a larger variance due to the errors in ranking the units. To reduce the errors in ranking in estima...

Some Estimators for the Population Mean Using Auxiliary Information Under Ranked Set Sampling