关键词: 抽样调查, 混合类型辅助变量, 模型校准, 非参数核回归

Abstract: In the super population model, the continuous variables are generally used as the auxiliary variables to build up models. However, there are very rare cases to study the models with the mixed auxiliary variables. In order to fully use the correlative information both related to continuous and discrete variables, a nonparametric model calibration estimator with mixed auxiliary variables is proposed in this paper by applying the methodology of nonparametric kernel regression under the framework of model calibration. The proposed estimator has been proved to be asymptotically unbiased, consistent and asymptotically normal as it is designed, together with its variance and its variance estimator.. The study with simulation data shows that the effect of the proposed estimator has been much improved whenever the total regression function is linear or nonlinear. In addition, the validation study with the CLHLS data justifies that the proposed estimator is better than that based only on the continuous auxiliary variables.

Key words: Sample Survey, Mixed Auxiliary Variable, Model Calibration, Nonparametric Kernel Regression