Nonparametric Regression: Optimal Local Bandwidth Choice
Journal of the Royal Statistical Society Series B (Statistical Methodology)Published 1 January 1991
Philippe Vieu
Citations70
SJR quartileQ1
SJR score3.31
SNIP2.48
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TL;DR
Kernel estimators of a regression function are investigated and this method is shown to be asymptotically optimal with respect to local quadratic measures of errors.
Abstract
SUMMARY Kernel estimators of a regression function are investigated. The bandwidths are locally chosen by a data-driven method based on the minimization of a local cross-validation criterion. This method is shown to be asymptotically optimal with respect to local quadratic measures of errors. Monte Carlo experiments are presented, and finally the method is applied to some data of medical interest.
Keywords
MathematicsEngineering
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