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Birke, Melanie
Year of Publication: 
Series/Report no.: 
Technical Report / Universität Dortmund, SFB 475 Komplexitätsreduktion in Multivariaten Datenstrukturen 2006,53
A central limit theorem for the weighted integrated squared error of kernel type estimators of the first two derivatives of a nonparametric regression function is proved by using results for martingale differences and U-statistics. The results focus on the setting of the Nadaraya-Watson estimator but can also be transfered to local polynomial estimates.
central limit theorem
integrated squared error
kernel estimates
local polynomial estimate
Nadaraya-Watson estimate
nonparametric regression
Document Type: 
Working Paper

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