Nonparametric identification for nonlinear autoregressive time series models: Convergence rates

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	Nonparametric identification for nonlinear autoregressive time series models: Convergence rates
	Lu, ZD; Cheng, P
	1999-04-01
发表期刊	CHINESE ANNALS OF MATHEMATICS SERIES B
ISSN	0252-9599
卷号	20 期号:2 页码:173-184
摘要	In this paper, the optimal convergence rates of estimators based on kernel approach for nonlinear AR model are investigated in the sense of Stone([17, 18]). By combining the alpha-mixing property of the stationary solution with the characteristics of the model itself, the restrictive conditions in the literature which are not easy to be satisfied by the nonlinear AR model are removed, and the mild conditions are obtained to guarantee the optimal rates of the estimator of autoregression function. In addition, the strongly consistent estimator of the variance of white noise is also constructed.
关键词	nonlinear AR model optimal convergence rates Kernel approach autoregression function variance of white noise consistency
语种	英语
WOS研究方向	Mathematics
WOS类目	Mathematics
WOS记录号	WOS:000080071600005
出版者	BALTZER SCI PUBL BV
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/14379
专题	中国科学院数学与系统科学研究院
作者单位	Acad Sinica, Inst Syst Sci, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Lu, ZD,Cheng, P. Nonparametric identification for nonlinear autoregressive time series models: Convergence rates[J]. CHINESE ANNALS OF MATHEMATICS SERIES B,1999,20(2):173-184.
APA	Lu, ZD,&Cheng, P.(1999).Nonparametric identification for nonlinear autoregressive time series models: Convergence rates.CHINESE ANNALS OF MATHEMATICS SERIES B,20(2),173-184.
MLA	Lu, ZD,et al."Nonparametric identification for nonlinear autoregressive time series models: Convergence rates".CHINESE ANNALS OF MATHEMATICS SERIES B 20.2(1999):173-184.