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.

引用

页码：626 / 640

页数：15

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