关键词: 抽样估计, 模型辅助, 半参数模型, 辅助信息

Abstract: Based on the existing model-assisted estimation method, a new model-assisted estimator is proposed by a semi-parametric superpopulation model and the generalized difference estimation. The new estimator uses the same auxiliary information as the generalized regression estimator, which uses less and easier auxiliary information than the classical nonparametric and semi-parametric regression estimators, but in general it is more accurate than the generalized regression estimator. The new estimator can be proved to be asymptotically design-unbiased and design consistent, and its asymptotic design mean square error is the variance of the generalized difference estimator. Simulation experiments indicate the following results about the new estimator: It is never worse than the generalized regression estimator; its accuracy has more obvious improvement than the generalized regression estimator for those superpopulation models linear degrees of which are the lower; in this simulation, smooth parameter which is properly selected between 0.04 and 0.12 can get good estimation effect relatively.

Key words: Sampling Estimation, Model-assisted, Semi-parametric Model, Auxiliary Information