Convergence rate of cross-validation in nonlinear wavelet regression estimation

作     者：Zhang Shuanglin Zheng Zhongguo 

作者机构：Peking Univ Dept Probabil & Stat Beijing 100871 Peoples R China 

出 版 物：《Chinese Science Bulletin》 (科学通报(英文版))

年 卷 期：1999年第44卷第10期

页      面：898-901页

核心收录：

学科分类：02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学] 

基　　金：49775261 National Natural Science Foundation of China,NSFC Natural Science Foundation of Heilongjiang Province State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,LASG: 49823002 

主　　题：wavelet estimation nonparametric regression estimators cross-validation strong consistency. 

摘      要：Cross-validation method is used to choose the three smoothing parameters in nonlin ear wavelet regression estimators. The strong consistency and convergence rate of cross-vali dation nonlinear wavelet regression estimators are obtained.