基于多重抽样框的连续性抽样估计方法研究

The Study of Successive Sampling Estimation Methods Based on Multiple Sampling Frames

多重抽样框可以解决单一抽样框难以完整覆盖流动性目标总体的难题,连续性抽样调查则可以获取变量的时序观测数据,对总体现象进行追踪调查。本文将多重抽样框调查与连续性抽样调查两种方法结合在一起进行研究,深入分析基于多重抽样框的连续性抽样估计方法。文章首先设计了连续性调查环境下总体结构变动表;然后,在简单随机抽样假定下的轮换样本调查情形开展研究,设计了14种参数缩减方法对构建的似然函数进行估计求解,并给出了估计量的迭代计算过程;最后,对本文的研究内容进行了总结与展望。

The multiple sampling frames may solve the difficult problem that the single sampling frame to cover the fluid goal overall completely with difficulty,and the successive sampling survey may gain the different time succession observation data,carries on the follow-up study to the overall.This paper carries on the research unifies two methods of the multiple sampling frame survey and the successive sampling survey,and analyses in depth succession sampling estimate methods based on multiple sampling frames.Firstly,the article designs the gross structure change table under the successive survey;then,carries on research of rotating panel survey base on the hypothesis of simple random sampling,designs fourteen parameter deflation method to estimate the likelihood function,and gives the estimator iterative computation process.Finally,gives the summary and the scope of the research contents.