kern(y, x = 0, h = 1)
kernd(X, x, h)
kdex(X, x, h)
distancevector(X, y, d = "euclid", na.rm = TRUE)
vecdist(X,Y)
mindist(X,y)
enorm(x)
kern
specifies the base kernel (by default Gaussian) used in
lpc
; kernd
is the corresponding multivariate product
kernel. kdex
is a pointwise multivariate kernel density estimator.
distancevector
makes use of function vdisseuclid
from Rpackage