Nonparametric Regression: Optimal Local Bandwidth Choice
- 1 January 1991
- journal article
- research article
- Published by Oxford University Press (OUP) in Journal of the Royal Statistical Society Series B: Statistical Methodology
- Vol. 53 (2) , 453-464
- https://doi.org/10.1111/j.2517-6161.1991.tb01837.x
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.This publication has 14 references indexed in Scilit:
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