Development of new stratified estimators that incorporate prior and auxiliary information for estimating population characteristics and its applications

在各个研究领域，经常采用分层随机抽样的抽样调查来估计人口特征。通过结合辅助变量，我们可以获得比通常的无偏估计更有效的估计量，如比率、回归和校准估计量。另一方面，由于经常定期进行抽样调查，我们通常有关于人口特征的先验信息。在本研究中，我们不仅利用辅助变量，而且利用先验信息开发了更有效的估计器。

In various research areas, sample surveys based on the stratified random sampling are often conducted to estimate population characteristics. We can obtain more effective estimators, such as ratio, regression, and calibration estimators, than usual unbiased estimators by incorporating auxiliary variables. On the other hand, it is often the case that we have prior information on population characteristics since sample surveys are often regularly conducted. In this research, we developed more effective estimators by using not only auxiliary variables but also prior information.