Statistical Inferences in a Partially Linear Model with Autoregressive Errors

作     者：Xiao-hui LIU Yu WANG Ya-wen FAN Yu-zi LIU Xiao-hui LIU;Yu WANG;Ya-wen FAN;Yu-zi LIU

作者机构：School of StatisticsJiangxi University of Finance and EconomicsNanchang 330013China Key Laboratory of Data Science in Finance and EconomicsJiangxi University of Finance and EconomicsNanchang 330013China 

出 版 物：《Acta Mathematicae Applicatae Sinica》 (应用数学学报（英文版）)

年 卷 期：2022年第38卷第4期

页      面：822-842页

核心收录：

学科分类：02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学] 

基　　金：supported by the NSF of China(Nos.11971208,11601197) the NSSF of China(Grant No.21&ZD152) the China Postdoctoral Science Foundation(Nos.2016M600511,2017T100475) the NSF of Jiangxi Province(Nos.2018ACB21002,20171ACB21030) the Post graduate Innovation Project of Jiangxi Province(No.YC2021CB124) 

主　　题：partially linear model autoregressive errors two-step procedure profile empirical likelihood 

摘      要：In this paper,we consider the statistical inferences in a partially linear model when the model error follows an autoregressive process.A two-step procedure is proposed for estimating the unknown parameters by taking into account of the special structure in *** the asymptotic matrix of the estimator for the parametric part has a complex structure,an empirical likelihood function is also *** derive the asymptotic properties of the related statistics under mild *** simulations,as well as a real data example,are conducted to illustrate the finite sample performance.