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
Institutions:	Sonderforschungsbereich 373, Quantifikation und Simulation ökonomischer Prozesse, Wirtschaftswissenschaftliche Fakultät
Subject:	second order minimax risk \| Adaptive estimation \| penalized likelihood

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Extent:	application/pdf
Series:	SFB 373 Discussion Papers.
Type of publication:	Book / Working Paper
Notes:	Number 1997,100
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010983808