Asymptotic Inference in the Random Coefficient Autoregressive Model with Time-functional Variance Noises  

作　　者：En-wen ZHU Zi-wei DENG Han-jun ZHANG Jun CAO Xiao-hui LIU 

机构地区：[1]Department of Mathematics and Statistics,Changsha University of Science and Technology,Changsha 410114,China [2]School of Mathematics and Computational Science,Xiangtan University,Xiangtan 411105,China [3]School of Statistics and Data Science,and Key Laboratory of Data Science in Finance and Economics,Jiangxi University of Finance and Economics,Nanchang 330013,China

出　　处：《Acta Mathematicae Applicatae Sinica》2024年第2期320-346,共27页应用数学学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant No.52338009);the National Science Fund for Distinguished Young Scholars(Grant No.52025085);the Graduate Research Innovation Project of Hunan Province(Grant No.CX20220952);Xiaohui Liu’s research is supported by the NSF of China(Grant No.11971208);the National Social Science Foundation of China(Grant No.21&ZD152);the Outstanding Youth Fund Project of the Science and Technology Department of Jiangxi Province(Grant No.20224ACB211003);the NSF of China(Grant No.92358303).

摘　　要：This paper considers the random coefficient autoregressive model with time-functional variance noises,hereafter the RCA-TFV model.We first establish the consistency and asymptotic normality of the conditional least squares estimator for the constant coefficient.The semiparametric least squares estimator for the variance of the random coefficient and the nonparametric estimator for the variance function are constructed,and their asymptotic results are reported.A simulation study is presented along with an analysis of real data to assess the performance of our method in finite samples.

关 键 词：random coefficient autoregressive model time-functional variance conditional least squares semiparametric least squares 

分 类 号：O212.1[理学—概率论与数理统计]