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학술저널
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한국자료분석학회 Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제15권 제4호
발행연도
2013.1
수록면
1,743 - 1,753 (11page)

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This study covers the sampling methods based on ranked set sampling (RSS) to estimate the population mean. The purpose of this study is to compare the relative efficiencies (RE) of several sampling methods which we consider in this paper and to find the sampling method with the best efficiency. Including the RSS, the extreme ranked set sampling (ERSS) proposed by Samawi et al. (1996), median ranked set sampling (MRSS) by Muttlak (1998), L ranked set sampling (LRSS) proposed by Al-Nasser (2007), adjusted ranked ordering set sampling (AROSS) proposed by Kim et al. (2007) and folded ranked set sampling (FRSS) proposed by Bani-Mustafa et al. (2011) are introduced and compared with each other in terms of the RE. First of all, we derive the RE for each sampling method analytically. Assuming that the distributions are symmetric about zero, Var(bar{X}_{MRSS}) is the smallest and Var(bar{X}_{LRSS}) is the second smallest, which means that the MRSS has the highest RE except for the AROSS. As a result, comparing the values of RE's for underlying distributions when the sample size is 3 to 6, we show that the AROSS has the best efficiency followed by the MRSS, LRSS, RSS, ERSS and FRSS for most distributions.

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