Asymptotic results of error density estimator in nonlinear autoregressive models

被引：1

作者：

Wu, Shipeng ^{[1
,2
]}

Yang, Wenzhi ^{[1
]}

Gao, Min ^{[1
]}

Fang, Hongyan ^{[1
]}

机构：

[1] Anhui Univ, Sch Big Data & Stat, Hefei, Peoples R China

[2] Shanxi Univ Finance & Econ, Sch Stat, Taiyuan, Peoples R China

来源：

JOURNAL OF THE KOREAN STATISTICAL SOCIETY | 2024年 / 53卷 / 03期

关键词：

Nonlinear autoregressive models; alpha-mixing; Kernel density estimator; Asymptotic normality; Uniform convergence rate; REGRESSION-MODEL; STRONG CONSISTENCY; NORMALITY; CONVERGENCE; THEOREM;

D O I：

10.1007/s42952-024-00258-3

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

This paper considers the asymptotic properties of the error density estimator in the nonlinear autoregressive models with alpha-mixing errors. The asymptotic distribution and uniform convergence rate for the kernel density estimator of error density function are obtained. Last, some simulations of histograms, confidence intervals and mean integrated square errors are illustrated, which agree with our theoretical results.

引用

页码：563 / 582

页数：20

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