Bandwidth selection for kernel conditional density estimation

David Bashtannyk, Rob J Hyndman
(2001) Computational Statistics and Data Analysis 36(3), 279-298

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


Errata:

  • $d$ should be $|d|$ in the normal reference rule formulae.