Estimation of partial derivative functionals with application to human mortality data analysis  

作　　者：Tao Zhang Zhaohai Li Aiyi Liu Qingzhao Zhang 

机构地区：[1]School of Science,Guangxi University of Science and Technology,Liuzhou,545006,China [2]Department of Statistics,George Washington University,Washington,DC,20052,USA [3]Department of Health and Human Services,National Institute of Child Health and Human Development,Bethesda,MD,20817,USA [4]Department of Statistics,School of Economics,Xiamen University,Xiamen,361005,China [5]MOE Key Laboratory of Econometrics,Xiamen University,Xiamen,361005,China [6]The Wang Yanan Institute for Studies in Economics,Xiamen University,Xiamen,361005,China

出　　处：《Science China Mathematics》2021年第9期2117-2140,共24页中国科学：数学（英文版）

基　　金：supported by National Natural Science Foundation of China(Grant Nos.11861014,11561006 and 11971404);Natural Science Foundation of Guangxi Province(Grant No.2018GXNSFAA281145);Humanity and Social Science Youth Foundation of Ministry of Education of China(Grant No.19YJC910010);the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development,National Institutes of Health,USA。

摘　　要：To better describe and understand the time dynamics in functional data analysis,it is often desirable to recover the partial derivatives of the random surface.A novel approach is proposed based on marginal functional principal component analysis to derive the representation for partial derivatives.To obtain the Karhunen-Lo`eve expansion of the partial derivatives,an adaptive estimation is explored.Asymptotic results of the proposed estimates are established.Simulation studies show that the proposed methods perform well in finite samples.Application to the human mortality data reveals informative time dynamics in mortality rates.

关 键 词：bivariate functional data functional principal component analysis MORTALITY partial derivatives 

分 类 号：R195.3[医药卫生—卫生统计学] O172.1[医药卫生—卫生事业管理]