On adaptive smoothing in partial linear models
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.
|Date of creation:||2001|
|Date of revision:|
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