Kernel Density Estimation for Demonstration Purposes
Description
Demonstration code showing how (univariate) kernel
density estimates are computed, at least conceptually,
and allowing users to experiment with different kernels,
should they so wish. The method used follows directly
the definition, but gains efficiency by replacing the
observations by frequencies in a very fine grid covering
the sample range. A canonical reference is
B. W. Silverman, (1998) .
NOTE: the density function in the
stats package uses a more sophisticated method based on the
fast Fourier transform and that function should be used if
computational efficiency is a prime consideration.