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基于Brewer抽样的不放回样本追加策略下域的估计
引用本文:李莉莉. 基于Brewer抽样的不放回样本追加策略下域的估计[J]. 数理统计与管理, 2017, 0(4): 651-660. DOI: 10.13860/j.cnki.sltj.20170517-003
作者姓名:李莉莉
作者单位:青岛大学经济学院,山东青岛,266101
基金项目:中国科技部“十二五”支撑计划项目(2014BAK01B04-2)
摘    要:本文研究了基于Brewer抽样的不放回追加策略,给出单元的前两阶包含概率的具体计算公式,并构造联合设计下的Horvitz-Thompson估计,同时给出了模拟结果。根据模拟结果可以看出,在联合设计下域总量估计的精度比基本设计和追加设计下估计量的精度高。

关 键 词:Brewer抽样  样本追加策略  域估计

Domain Estimation Based on Brewer Sampling without Replacement Complementing Strategies
Abstract:This paper develops complementing strategies of sampling without replacement based on the Brewer sampling.The specific calculation formula of the first (second)-order inclusion probability of the unit and the Horvitz-Thompson estimator under the joint-design are given.Simulation results are conducted at the same time.The simulation results show that the estimator under the joint-design is more precise than the estimator under the basic design and the complement design.
Keywords:Brewer sampling  complementing strategies of sampling  domain estimation
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