Research On The Auxiliary Information Application To The Domain Estimation Models And Methodologies

The paper systematically dissert various auxiliary information application models and methods in domain estimation. The system is new, and the point of view is also new.First, the paper summarizes the background of this topic, the purport of this research, and the theory and practice status quo of this field. Then gives some definitions such as domain, small domain, small area, auxiliary information, and introduces the sources, functions, applicability conditions and limitations of the auxiliary information. Thirdly, classifies the methods of domain estimation into two types: direct estimation method and indirect estimation method. Moreover, the latter method can be classified into implicit model estimate method and the explicit model estimate method. The article emphasizes the function of the auxiliary information in the domain estimation. Based on this purpose, the author separately discusses some direct estimation methods such as Calibration Estimation Method, Generalized Regression Estimation Method etc. and some indirect estimation methods such as Demographic Method, Synthetic Estimation Method, Composite Estimation Method, James-Stein Method (or Shrinkage Method) etc. which are all implicit model estimate methods, and some explicit model estimate methods, include area level linear mixed model and unit level linear mixed model. Fourthly, this paper gives some brief summary and contrast analysis of the direct estimation method and indirect estimation method, the implicit model and explicit model, and the area level model estimation and the unit level model estimation. Fifthly, paper gives some parameter estimation methods such as the Empirical Best Linear Unbiased Prediction method (EBLUP), Empirical Bayes method (EB) and Hierarchical Bayes method (HB). Finally, the author sum up some problems, points some shortcomings and prospects the theory development and applications of these methods.