On adaptive estimation in partial linear models

The problem of estimation of the finite dimensional parameter in a partial linear model is considered. We derive upper and lower bounds for the second minimax order risk and show that the second order minimax estimator is a penalized maximum likelihood estimator. It is well known that the performance of the estimator is depending on the choice of a smoothing parameter. We propose a practically feasible adaptive procedure for the penalization choice.

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Year of publication:	1997
Authors:	Golubev, Georgi ; Härdle, Wolfgang
Publisher:	Berlin : Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes
Subject:	second order minimax risk \| Adaptive estimation \| penalized likelihood

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Series:	SFB 373 Discussion Paper ; 1997,100
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	729738442 [GVK] hdl:10419/66264 [Handle] RePEc:zbw:sfb373:1997100 [RePEc]
Source:	EconStor

Persistent link: https://www.econbiz.de/10010310782