On the Ranked-Set Sampling M-Estimates for Symmetric Location Families

被引：0
|
作者：
Xiaoyue Zhao
Zehua Chen
机构：
[1] University of California,Department of Statistics
[2] National University of Singapore,Department of Statistics & Applied Probability
来源：
Annals of the Institute of Statistical Mathematics | 2002年 / 54卷
关键词：
Asymptotic normality; asymptotic relative efficiency; M-estimates; optimal sampling design; ranked-set sampling; robustness;
D O I：
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摘要：
The ranked-set sampling (RSS) is applicable in practical problems where the variable of interest for an observed item is costly or time-consuming but the ranking of a set of items according to the variable can be easily done without actual measurement. In this article, the M-estimates of location parameters using RSS data are studied. We deal mainly with symmetric location families. The asymptotic properties of M-estimates based on ranked-set samples are established. The properties of unbalanced ranked-set sample M-estimates are employed to develop the methodology for determining optimal ranked-set sampling schemes. The asymptotic relative efficiencies of ranked-set sample M-estimates are investigated. Some simulation studies are reported.
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页码：626 / 640
页数：14
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