摘要
抽样调查中基于模型推断方法获得的估计量性质是依赖于模型的。在恰当的模型下比率估计和扩张估计是最优线性无偏估计。当模型设定错误时,比率估计和扩张估计是有偏估计,但如果样本是平衡的,可以消除偏倚,从而实现了复杂问题简单处理的思想。
Properties of model-based estimator in survey sampling depends on assumption of model.Ratio estimator or expansion estimator is best linear unbiased estimator under appropriate model.A bias is incurred when the model is wrong.The possibility of such a bias is avoided by balanced sample.Consequently,the idea that complex question is solved simply is achieved.
出处
《统计与信息论坛》
CSSCI
2012年第3期38-42,共5页
Journal of Statistics and Information
基金
国家社科基金项目<普查数据质量的事后抽查理论及其应用研究>(11BTJ009)
教育部人文社科基地重大项目<复杂抽样中的模型方法研究>(10JJD790036)
关键词
超总体
比率估计
扩张估计
平衡样本
superpopulation
ratio estimator
expansion estimator
balanced sample