Model-Assisted Estimators with Auxiliary Functional Data  

作　　者：Chao Liu Huiming Zhang Jing Yan 

机构地区：[1]Department of Statistics and Data Science,Southern University of Science and Technology,Shenzhen 518055,China [2]Pepartment of Mathematics,Faculty of Science and Techmnology,University of Macao,Taipa Macao,China [3]UMacao Zhuhai Research Institute,Zhuhai,China [4]School of Mathematics and Statistics,Beijing Institute of Technology,Beijing,China

出　　处：《Communications in Mathematical Research》2022年第1期81-98,共18页数学研究通讯（英文版）

基　　金：China Postdoctoral Science Foundation(Grant Nos.2021M691443,2021TQ0141);SUSTC Presidential Postdoctoral Fellow-ship.Huiming Zhang was supported in part by the University of Macao under UM Macao Talent Programme(UMMTP-2020-01).

摘　　要：Few studies focus on the application of functional data to the field of design-based survey sampling.In this paper,the scalar-onunction regression model-assisted method is proposed to estimate the finite population means with auxiliary functional data information.The functional principal component method is used for the estimation of functional linear regression model.Our proposed functional linear regression model-assisted(FLR-assisted)estimator is asymptotically design-unbiased,consistent under mild conditions.Simulation experiments and real data analysis show that the FLR-assisted estimators are more efficient than the Horvitz-Thompson estimators under different sampling designs.

关 键 词：Survey sampling semi-supervised inference model-assisted estimator Horvitz-Thompson estimator functional linear regression 

分 类 号：O174.5[理学—数学]