On adaptive smoothing in partial linear models
AbstractWe 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 InfoPaper 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.
Date of creation: 2001
Date of revision:
Partial linear model; second order minimax risk; adaptive estimation;
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