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

被引：0

作者：

Zhu, En-wen ^{[1
]}

Deng, Zi-wei ^{[1
]}

Zhang, Han-jun ^{[2
]}

Cao, Jun ^{[1
]}

Liu, Xiao-hui ^{[3
,4
]}

机构：

[1] Changsha Univ Sci & Technol, Dept Math & Stat, Changsha 410114, Peoples R China

[2] Xiangtan Univ, Sch Math & Computat Sci, Xiangtan 411105, Peoples R China

[3] Jiangxi Univ Finance & Econ, Sch Stat & Data Sci, Nanchang 330013, Peoples R China

[4] Jiangxi Univ Finance & Econ, Key Lab Data Sci Finance & Econ, Nanchang 330013, Peoples R China

来源：

ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES | 2024年 / 40卷 / 02期

基金：

中国国家自然科学基金;

关键词：

random coefficient autoregressive model; time-functional variance; conditional least squares; semiparametric least squares; ADAPTIVE ESTIMATION; STATISTICAL-INFERENCE; REGRESSION; HETEROSCEDASTICITY; NONSTATIONARITIES; VOLATILITY; SERIES;

D O I：

10.1007/s10255-024-1072-0

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

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.

引用

页码：320 / 346

页数：27

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