首页|Asymptotic normality of error density estimator in stationary and explosive autoregressive models

Asymptotic normality of error density estimator in stationary and explosive autoregressive models

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In this paper,we consider the limit distribution of the error density function estima-tor in the first-order autoregressive models with negatively associated and positively associated random errors.Under mild regularity assumptions,some asymptotic normality results of the residual density estimator are obtained when the autoregressive models are stationary process and explosive process.In order to illustrate these results,some simulations such as confidence intervals and mean integrated square errors are provided in this paper.It shows that the residual density estimator can replace the density"estimator"which contains errors.

explosive autoregressive modelsresidual density estimatorasymptotic distributionassociation sequence

WU Shi-peng、YANG Wen-zhi、GAO Min、HU Shu-he

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School of Mathematical Sciences & School of Big Data and Statistics,Anhui University,Hefei 230601,China

School of Statistics,Shanxi University of Finance and Economics,Taiyuan,030006,China

National Natural Science Foundation of ChinaNational Natural Science Foundation of Anhui ProvinceScience and Technology Innovation Project of Shanxi Province Universities

117010042008085MA142023L165

2024

10.1007/s11766-024-4558-x

高校应用数学学报B辑(英文版)
浙江大学 中国工业与应用数学学会

高校应用数学学报B辑(英文版)

影响因子：0.146
ISSN：1005-1031
年,卷(期)：2024.39(1)
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