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》 (中国科学通报)

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：National Natural Scienre Foundation of China, (49775261) State Education Commission of China 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) State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, LASG 

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.