Two stage ranked set sampling for estimating the population median

McIntyre was the first to suggest ranked set sampling (RSS) method for estimating the population mean. In this paper, we modify RSS to come up with new sampling method, namely, two stage ranked set sampling (TSRSS) for samples of size . The TSRSS is suggested for estimating the population median in...

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Main Authors: Abdul Aziz Jemain, Amer Al-Omari, Kamarulzaman Ibrahim
Format: Article
Published: Universiti Kebangsaan Malaysia 2008
Online Access:http://journalarticle.ukm.my/5126/
http://journalarticle.ukm.my/5126/
id ukm-5126
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spelling ukm-51262012-06-18T03:49:36Z http://journalarticle.ukm.my/5126/ Two stage ranked set sampling for estimating the population median Abdul Aziz Jemain, Amer Al-Omari , Kamarulzaman Ibrahim, McIntyre was the first to suggest ranked set sampling (RSS) method for estimating the population mean. In this paper, we modify RSS to come up with new sampling method, namely, two stage ranked set sampling (TSRSS) for samples of size . The TSRSS is suggested for estimating the population median in order to increase the efficiency of the estimators. The TSRSS was compared to the simple random sampling (SRS), ranked set sampling (RSS), extreme ranked set sampling (ERSS), median ranked set sampling (MRSS) and balance groups ranked set sampling (BGRSS) methods. It is found that, TSRSS gives an unbiased estimator of the population median of symmetric distributions and it is more efficient than SRS. Also, it is more efficient than RSS, ERSS, MRSS and BGRSS based on the same number of measured units. For asymmetric distributions considered in this study, TSRSS has a small bias and smaller variance than SRS, RSS, ERSS, MRSS and BGRSS methods. Universiti Kebangsaan Malaysia 2008 Article PeerReviewed Abdul Aziz Jemain, and Amer Al-Omari , and Kamarulzaman Ibrahim, (2008) Two stage ranked set sampling for estimating the population median. Sains Malaysiana, 37 (1). pp. 95-99. ISSN 0126-6039 http://www.ukm.my/jsm/english_journals/vol37num1_2008/vol37num2_07page95-99.html
repository_type Digital Repository
institution_category Local University
institution Universiti Kebangasaan Malaysia
building UKM Institutional Repository
collection Online Access
description McIntyre was the first to suggest ranked set sampling (RSS) method for estimating the population mean. In this paper, we modify RSS to come up with new sampling method, namely, two stage ranked set sampling (TSRSS) for samples of size . The TSRSS is suggested for estimating the population median in order to increase the efficiency of the estimators. The TSRSS was compared to the simple random sampling (SRS), ranked set sampling (RSS), extreme ranked set sampling (ERSS), median ranked set sampling (MRSS) and balance groups ranked set sampling (BGRSS) methods. It is found that, TSRSS gives an unbiased estimator of the population median of symmetric distributions and it is more efficient than SRS. Also, it is more efficient than RSS, ERSS, MRSS and BGRSS based on the same number of measured units. For asymmetric distributions considered in this study, TSRSS has a small bias and smaller variance than SRS, RSS, ERSS, MRSS and BGRSS methods.
format Article
author Abdul Aziz Jemain,
Amer Al-Omari ,
Kamarulzaman Ibrahim,
spellingShingle Abdul Aziz Jemain,
Amer Al-Omari ,
Kamarulzaman Ibrahim,
Two stage ranked set sampling for estimating the population median
author_facet Abdul Aziz Jemain,
Amer Al-Omari ,
Kamarulzaman Ibrahim,
author_sort Abdul Aziz Jemain,
title Two stage ranked set sampling for estimating the population median
title_short Two stage ranked set sampling for estimating the population median
title_full Two stage ranked set sampling for estimating the population median
title_fullStr Two stage ranked set sampling for estimating the population median
title_full_unstemmed Two stage ranked set sampling for estimating the population median
title_sort two stage ranked set sampling for estimating the population median
publisher Universiti Kebangsaan Malaysia
publishDate 2008
url http://journalarticle.ukm.my/5126/
http://journalarticle.ukm.my/5126/
first_indexed 2023-09-18T19:43:26Z
last_indexed 2023-09-18T19:43:26Z
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