Bayes Estimation of the Mean of Normal Distribution Using Moving Extreme Ranked Set Sampling

Amer Al-Omari, Said Al-Hadhrami

Abstract


Moving extreme ranked set sampling (MERSS) is one of useful modifications of ranked set sampling (RSS). The method has been investigated by many authors and proved to be a good competitor to simple random sampling (SRS). In this paper, Bayes estimation of the mean of normal distribution based on MERSS is considered and compared with SRS counterpart. The suggested estimators are found to be more efficient than that from SRS.


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DOI: http://dx.doi.org/10.18187/pjsor.v8i1.227

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Title

Bayes Estimation of the Mean of Normal Distribution Using Moving Extreme Ranked Set Sampling

Keywords


Description

Moving extreme ranked set sampling (MERSS) is one of useful modifications of ranked set sampling (RSS). The method has been investigated by many authors and proved to be a good competitor to simple random sampling (SRS). In this paper, Bayes estimation of the mean of normal distribution based on MERSS is considered and compared with SRS counterpart. The suggested estimators are found to be more efficient than that from SRS.


Date

2012-01-03

Identifier


Source

Pakistan Journal of Statistics and Operation Research; Vol 8. No. 1, 2012



Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810