序集抽样中M估计分布的随机加权逼近

吴耀华;刘驰宇

系统科学与数学 ›› 2009, Vol. 29 ›› Issue (5) : 693-705.

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系统科学与数学 ›› 2009, Vol. 29 ›› Issue (5) : 693-705. DOI: 10.12341/jssms08409
论文

序集抽样中M估计分布的随机加权逼近

    吴耀华, 刘驰宇
作者信息 +

Approximation to the Distribution of M-Estimates in Ranked-Set Sampling by Randomly Weighted Bootstrap

    WU Yaohua, LIU Chiyu
Author information +
文章历史 +

摘要

序集抽样是一种适用于准确测量花费太高而排序费用可以忽略不记时的一种抽样方法.讨论了序集抽样下的对于一般分布族M估计的相合性和渐近正态性并且通过随机加权的方法来估计M估计的分布.

Abstract

Ranked-Set Sampling(RSS) is a sampling method when a set of sampling units drawn from the population can be ranked by certain means rather cheaply without the actual measurement of the variable of interest which is costly
and/or time consuming. This paper is concerned with the consistency and asymptotic normality on the RSS M-estimates and approximation to its distribution by randomly weighted bootstrap.

关键词

序集抽样 / M估计 / 随机加权 / 渐近正态性.

Key words

Ranked-Set sampling / M-estimates / randomly weighted bootstrap / asymptotic normality.

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吴耀华 , 刘驰宇. 序集抽样中M估计分布的随机加权逼近. 系统科学与数学, 2009, 29(5): 693-705. https://doi.org/10.12341/jssms08409
WU Yaohua , LIU Chiyu. Approximation to the Distribution of M-Estimates in Ranked-Set Sampling by Randomly Weighted Bootstrap. Journal of Systems Science and Mathematical Sciences, 2009, 29(5): 693-705 https://doi.org/10.12341/jssms08409
中图分类号： 62E17    62G06   
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