%0 Journal Article
%T Approximation to the Distribution of M-Estimates in Ranked-Set Sampling by Randomly Weighted Bootstrap<br>序集抽样中$M$估计分布的随机加权逼近
%A WU Yaohua
%A LIU Chiyu
%A <br>吴耀华
%A 刘驰宇
%J 系统科学与数学
%D 2009
%I 
%X 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 costlyand/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.
%K Ranked-Set sampling
%K M-estimates
%K randomly weighted bootstrap
%K asymptotic normality<br>序集抽样
%K M估计
%K 随机加权
%K 渐近正态性.
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=37F46C35E03B4B86&jid=0CD45CC5E994895A7F41A783D4235EC2&aid=3FC6A94F5DE34EF122D1529128085C19&yid=DE12191FBD62783C&vid=771469D9D58C34FF&iid=94C357A881DFC066&sid=99A964928ADB4E67&eid=703F3C1B6594BA64&journal_id=1000-0577&journal_name=系统科学与数学&referenced_num=0&reference_num=19