Functional-coefficient partially linear regression model
文献类型：期刊论文
| 作者 | Wong, Heung1; Zhang, Riquan2,3; Ip, Wai-cheung1; Li, Guoying4 |
| 刊名 | JOURNAL OF MULTIVARIATE ANALYSIS
 |
| 出版日期 | 2008-02-01 |
| 卷号 | 99期号:2页码:278-305 |
| 关键词 | Back-fitting technique Functional-coefficient model Local linear polynomial technique Nonlinear time series |
| ISSN号 | 0047-259X |
| DOI | 10.1016/j.jmva.2007.03.003 |
| 英文摘要 | In this paper, the functional-coefficient partially linear regression (FCPLR) model is proposed by combining nonparametric and functional-coefficient regression (FCR) model. It includes the FCR model and the nonparametric regression (NPR) model as its special cases. It is also a generalization of the partially linear regression (PLR) model obtained by replacing the parameters in the PLR model with some functions of the covariates. The local linear technique and the integrated method are employed to give initial estimators of all functions in the FCPLR model. These initial estimators are asymptotically normal. The initial estimator of the constant part function shares the same bias as the local linear estimator of this function in the univariate nonparametric model, but the variance of the former is bigger than that of the latter. Similarly, initial estimators of every coefficient function share the same bias as the local linear estimates in the univariate FCR model, but the variance of the former is bigger than that of the latter. To decrease the variance of the initial estimates, a one-step back-fitting technique is used to obtain the improved estimators of all functions. The improved estimator of the constant part function has the same asymptotic normality property as the local linear nonparametric regression for univariate data. The improved estimators of the coefficient functions have the same asymptotic normality properties as the local linear estimates in FCR model. The bandwidths and the smoothing variables are selected by a data-driven method. Both simulated and real data examples related to nonlinear time series modeling are used to illustrate the applications of the FCPLR model. (C) 2007 Elsevier Inc. All rights reserved. |
| WOS研究方向 | Mathematics |
| 语种 | 英语 |
| WOS记录号 | WOS:000264679600006 |
| 出版者 | ELSEVIER INC |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/5463]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 通讯作者 | Wong, Heung |
| 作者单位 | 1.Hong Kong Polytech Univ, Dept Math Appl, Kowloon, Hong Kong, Peoples R China 2.Shanxi Datong Univ, Dept Math, Datong 037009, Shanxi, Peoples R China 3.E China Normal Univ, Dept Stat, Shanghai 200062, Peoples R China 4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wong, Heung,Zhang, Riquan,Ip, Wai-cheung,et al. Functional-coefficient partially linear regression model[J]. JOURNAL OF MULTIVARIATE ANALYSIS,2008,99(2):278-305. |
| APA | Wong, Heung,Zhang, Riquan,Ip, Wai-cheung,&Li, Guoying.(2008).Functional-coefficient partially linear regression model.JOURNAL OF MULTIVARIATE ANALYSIS,99(2),278-305. |
| MLA | Wong, Heung,et al."Functional-coefficient partially linear regression model".JOURNAL OF MULTIVARIATE ANALYSIS 99.2(2008):278-305. |
入库方式： OAI收割
来源：数学与系统科学研究院
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