中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Nonparametric identification for nonlinear autoregressive time series models: Convergence rates

文献类型:期刊论文

作者Lu, ZD; Cheng, P
刊名CHINESE ANNALS OF MATHEMATICS SERIES B
出版日期1999-04-01
卷号20期号:2页码:173-184
关键词nonlinear AR model optimal convergence rates Kernel approach autoregression function variance of white noise consistency
ISSN号0252-9599
英文摘要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.
WOS研究方向Mathematics
语种英语
WOS记录号WOS:000080071600005
出版者BALTZER SCI PUBL BV
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/14378]  
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.

入库方式: OAI收割

来源:数学与系统科学研究院

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