nonparametricidentificationfornonlinearautoregressivetimeseriesmodelsconvergencerates
文献类型：期刊论文
| 作者 | Cheng Ping; Lu Zudi |
| 刊名 | chineseannalsofmathematicsseriesb
 |
| 出版日期 | 1999 |
| 卷号 | 20期号:2页码:173 |
| 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. |
| 语种 | 英语 |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/47251]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 作者单位 | 中国科学院数学与系统科学研究院 |
| 推荐引用方式 GB/T 7714 | Cheng Ping,Lu Zudi. nonparametricidentificationfornonlinearautoregressivetimeseriesmodelsconvergencerates[J]. chineseannalsofmathematicsseriesb,1999,20(2):173. |
| APA | Cheng Ping,&Lu Zudi.(1999).nonparametricidentificationfornonlinearautoregressivetimeseriesmodelsconvergencerates.chineseannalsofmathematicsseriesb,20(2),173. |
| MLA | Cheng Ping,et al."nonparametricidentificationfornonlinearautoregressivetimeseriesmodelsconvergencerates".chineseannalsofmathematicsseriesb 20.2(1999):173. |
入库方式： OAI收割
来源：数学与系统科学研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。