中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Spatial Nonparametric Regression Estimation: Non-isotropic Case

文献类型:期刊论文

作者Lu Zudi2; Chen Xing1
刊名Acta Mathematicae Applicatae Sinica
出版日期2002
卷号18期号:4页码:641-656
关键词bandwidth kernel estimator mixing non-isotropic spatial data spatial conditional regression weak consistency and rates
ISSN号0168-9673
其他题名Spatial Nonparametric Regression Estimation: Non-isotropic Case
英文摘要Data collected on the surface of the earth often has spatial interaction. In this paper, a non-isotropic mixing spatial data process is introduced, and under such a spatial structure a nonparametric kernel method is suggested to estimate a spatial conditional regression. Under mild regularities, sufficient conditions are derived to ensure the weak consistency as well as the convergence rates for the kernel estimator. Of interest are the following: (1) All the conditions imposed on the mixing coefficient and the bandwidth are simple; (2) Differently from the time series setting, the bandwidth is found to be dependent on the dimension of the site in space as well; (3) For weak consistency, the mixing coefficient is allowed to be unsummable and the tendency of sample size to infinity may be in different manners along different direction in space; (4) However, to have an optimal convergence rate, faster decreasing rates of mixing coefficient and the tendency of sample size to infinity along each direction are required.
语种英语
CSCD记录号CSCD:1367037
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/53042]  
专题中国科学院数学与系统科学研究院
作者单位1.云南大学
2.中国科学院数学与系统科学研究院
推荐引用方式
GB/T 7714
Lu Zudi,Chen Xing. Spatial Nonparametric Regression Estimation: Non-isotropic Case[J]. Acta Mathematicae Applicatae Sinica,2002,18(4):641-656.
APA Lu Zudi,&Chen Xing.(2002).Spatial Nonparametric Regression Estimation: Non-isotropic Case.Acta Mathematicae Applicatae Sinica,18(4),641-656.
MLA Lu Zudi,et al."Spatial Nonparametric Regression Estimation: Non-isotropic Case".Acta Mathematicae Applicatae Sinica 18.4(2002):641-656.

入库方式: OAI收割

来源:数学与系统科学研究院

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