Multistage Median Ranked Set Sampling for Estimating the Population Median
Abdul Aziz Jemain, Amer Al-Omari and Kamarulzaman Ibrahim
DOI : 10.3844/jmssp.2007.58.64
Journal of Mathematics and Statistics
Volume 3, Issue 2
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 found that MMRSS gives an unbiased estimate of the population median of symmetric distributions and it is more efficient than SRS, RSS and MRSS based on the same number of measured units. Also, it was found that the efficiency of MMRSS increases in r (r is the number of stage) for specific value of the sample size. For asymmetric distributions considered in this study, MMRSS has a small bias, close to zero as r increases, especially with odd sample size. A set of real data was used to illustrate the method.
© 2007 Abdul Aziz Jemain, Amer Al-Omari and Kamarulzaman Ibrahim. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.