Bandwidth selection for kernel conditional density estimation

Authors

David Bashtannyk, Rob J Hyndman

Published

16 June 2001

Publication details

Computational Statistics and Data Analysis 36(3), 279-298

Links

DOI

 

We consider bandwidth selection for the kernel estimator of conditional density with one explanatory variable. Several bandwidth selection methods are derived ranging from fast rules-of-thumb which assume the underlying densities are known to relatively slow procedures which use the bootstrap. The methods are compared and a practical bandwidth selection strategy which combines the methods is proposed. The methods are compared using two simulation studies and a real data set.

Keywords: density estimation; kernel smoothing; conditioning; bandwidth selection.

R code


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