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

被引：1

作者：

Al-Hadhrami, Said Ali ^{[1
]}

Al-Omari, Amer Ibrahim ^{[2
]}

机构：

[1] Coll Appl Sci Nizwa, Muscat, Oman

[2] Al Al Bayt Univ, Dept Math, Mafraq, Jordan

来源：

PAKISTAN JOURNAL OF STATISTICS AND OPERATION RESEARCH | 2012年 / 8卷 / 01期

关键词：

Moving extreme ranked set sampling; Bayes estimator; Efficiency;

D O I：

暂无

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Moving extreme ranked set sampling(MERSS)(Al-Saleh and Al-Hadrami 2003 a, b) is one of useful modifications of the usualranked setsampling(RSS). This method uses only extremes ranks with varied set size to reduce error in ranking. In this paper, Bayes estimation of the mean of normal distribution based on MERSSwas considered and compared with simple random sampling (SRS). counterpart. The suggested estimatorsare found to be more efficient than that from SRS.

引用

页码：21 / 30

页数：10

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