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On adaptive smoothing in partial linear models

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  • Golubev, Georgi
  • Härdle, Wolfgang

Abstract

We consider a problem of estimation of parametric components in a partial linear model. Suppose that a finite set E of linear estimators is given. Our goal is to mimic the estimator in E that has the smallest risk. Using a second order expansion of the risk of linear estimators we propose a practically feasible adaptive procedure for choice of smoothing parameters based on the principle of unbiased risk estimation. --

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Bibliographic Info

Paper provided by Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes in its series SFB 373 Discussion Papers with number 2001,48.

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Date of creation: 2001
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Handle: RePEc:zbw:sfb373:200148

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Keywords: Partial linear model; second order minimax risk; adaptive estimation;

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