1. Maximum ranked set sampling for estimating population maximum
Authors : Jaya Laxman Limbore
Pages : 18-23
Keywords : Ranked Set Sampling, Simple Random Sampling, Maximum Ranked Set Sampling, Sample Maximum, Expected Value, Sampling Variance, Relative Efficiency Abstract :
Ranked set sampling (RSS) was initially proposed by McIntyre (1952) for estimating the population mean when measurement is far more costly than judgmentally comparing and ranking sampling units. It has been established in the statistical literature that ranked set sampling provides a more efficient estimator of the population mean than simple random sampling (SRS). When the purpose of sampling is to estimate the population maximum, a variation of ranked set sampling, called maximum ranked set sampling (MRSS) has been pro-posed. This paper investigates the sampling properties of the sample maximum under MRSS. The expected value and sampling variance of the sample maximum are derived under MRSS and are compared with the corresponding quantities for simple random sampling and ranked set sampling.
Citing this Journal Article :Jaya Laxman Limbore, "Maximum ranked set sampling for estimating population maximum", Volume 6 Issue 4 - March 2016, 18-23
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