On the ranked-set sampling M-estimates for symmetric location families

被引：3
|
作者：
Zhao, XY
Chen, ZH
机构：
[1] Univ Calif Berkeley, Dept Stat, Berkeley, CA 94720 USA
[2] Natl Univ Singapore, Dept Stat & Appl Probabil, Singapore 117543, Singapore
来源：
ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS | 2002年 / 54卷 / 03期
关键词：
asymptotic normality; asymptotic relative efficiency; M-estimates; optimal sampling design; ranked-set sampling; robustness;
D O I：
10.1023/A:1022423429880
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：
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：15
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