Bootstrap selection of bandwidth and confidence bands for nonparametric regression
- 1 October 1990
- journal article
- research article
- Published by Taylor & Francis in Journal of Statistical Computation and Simulation
- Vol. 37 (1-2) , 37-44
- https://doi.org/10.1080/00949659008811292
Abstract
A bootstrap method is developed to estimate the average squared error of a kernel based nonparametric regression estimator for a given bandwidth. This estimated average squared error is then minimised over the bandwidth to produce a regression estimate. Locally adaptive smoothing and simultaneous confidence bands may be obtained from this bootstrap method.Keywords
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