Publication details

Problems of automatic data-driven bandwidth selectors for nonparametric regression



Year of publication 2002
Type Article in Periodical
Magazine / Source Journal of Electrical Engineering
MU Faculty or unit

Faculty of Science

Field Applied statistics, operation research
Keywords Nonparametric regression; data driven bandwidth selector; Fourier transformation
Description This note is concerned with the problem of automatic data-driven bandwidth selectors for nonparametric regression. Some selectors were shown to be consistent and asymptotically unbiased by Rice (1984) and H\"ardle (1990). However, in simulation studies, it is often observed that most selectors are biased toward undersmoothing and give smaller bandwidths more frequently than predicted by asymptotic results.This motivates us to study the causes of undersmoothing. An explanation for the difficulty is given here. The Fourier transformation is used for a remedy. This leads to the consideration of a new procedure which is simple modification of a classical selector. A simulation study suggests that the proposed selector is much more consistent than the classical one.
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