bkfe {KernSmooth}  R Documentation 
Returns an estimate of a binned approximation to the kernel estimate of the specified density functional. The kernel is the standard normal density.
bkfe(x, drv, bandwidth, gridsize = 401, range.x, binned = FALSE, truncate = TRUE)
x 
vector of observations from the distribution whose density is to be estimated. Missing values are not allowed. 
drv 
order of derivative in the density functional. Must be a nonnegative even integer. 
bandwidth 
the kernel bandwidth smoothing parameter. 
gridsize 
the number of equallyspaced points over which binning is performed. 
range.x 
vector containing the minimum and maximum values of x
at which to compute the estimate.
The default is the minimum and maximum data values, extended by the
support of the kernel.

binned 
logical flag: if TRUE , then x and y are taken to be grid counts
rather than raw data.

truncate 
logical flag: if TRUE , data with x values outside the
range specified by range.x are ignored.

The density functional of order drv
is the integral of the
product of the density and its drv
th derivative.
The kernel estimates
of such quantities are computed using a binned implementation,
and the kernel is the standard normal density.
the estimated functional.
Estimates of this type were proposed by Sheather and Jones (1991).
Sheather, S. J. and Jones, M. C. (1991). A reliable databased bandwidth selection method for kernel density estimation. Journal of the Royal Statistical Society, Series B, 53, 683–690.
Wand, M. P. and Jones, M. C. (1995). Kernel Smoothing. Chapman and Hall, London.
data(geyser, package="MASS") x < geyser$duration est < bkfe(x, drv=4, bandwidth=0.3)