Central limit theorems for the integrated squared error of derivative estimators

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.

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Year of publication:	2006
Authors:	Birke, Melanie
Publisher:	Dortmund : Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Subject:	central limit theorem \| integrated squared error \| kernel estimates \| local polynomial estimate \| Nadaraya-Watson estimate \| nonparametric regression

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Series:	Technical Report ; 2006,53
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	534715818 [GVK] hdl:10419/22697 [Handle] RePEc:zbw:sfb475:200653 [RePEc]
Source:	EconStor

Persistent link: https://www.econbiz.de/10010296768