On adaptive smoothing in partial linear models

Georgi Golubev and Wolfgang Härdle

No 2001,48, SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

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.

Keywords: Partial linear model; second order minimax risk; adaptive estimation (search for similar items in EconPapers)
Date: 2001
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb373:200148

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