SFB 303 Discussion Paper No. A - 200

Author: Härdle, W., J. D. Hart, J. S. Marron, and A. B. Tsybakov
Title: Bandwidth Choice for Average Derivative Estimation
Abstract: The average derivative is the expected value of the derivative of a regression function. Kernel methods have been proposed as a means of estimating this quantity. The problem of bandwidth selection for these kernel estimators is addressed here. Asymptotic representations are found for the variance and squared bias. These are compared with each other, to find an insightful representation for the optimal bandwidth. The extent to which the theoretical conclusions apply in practice is investigated in an important economical example related to the Law of Demand.
Creation-Date: March 1989 
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