Approximation to the Distribution of M-Estimates in Ranked-Set Sampling by Randomly Weighted Bootstrap
序集抽样中$M$估计分布的随机加权逼近

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.