| Library: | smoother |
| See also: | Rdenbest denxbwcrit denxest |
| Quantlet: | Rdenxest | |
| Description: | evaluates a kernel estimate of an integrated squared density (derivative) using the normal kernel for a (vector of) bandwidth(s) h. |
| Usage: | Rh = Rdenxest(der, x, h, diag) | |
| Input: | ||
| der | scalar, order of derivative der = 0,1,2,... | |
| x | n x 1 vector of data points | |
| h | p x 1 vector of bandwidths | |
| diag | scalar, if set to 0, the diagonal terms are removed from the estimate, otherwise included | |
| Output: | ||
| Rh | p x 1 vector of the functional estimates | |
library("smoother")
library("xplore")
randomize(0)
n = 100
s = 2
diag = 1
h = #(0.1, 0.2, 0.3)
{w,mu,sigma}=normalmixselect("Marron_Wand_3")
x = normalmix(n,w,mu,sigma)
Rh = Rdenxest(s,x,h,diag)
h ~ Rh
kernel estimates for the integrated squared second density derivative for three different bandwidths are computed which are based on a sample of size 100 generated from a normal mixture example density: Contents of _tmp [1,] 0.1 1742 [2,] 0.2 111.71 [3,] 0.3 18.953