Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Library: cafpe
See also: tp/cafpe/fvllc

Quantlet: dencp
Description: Quantlet for multivariate density estimation using kernel estimation using C++ routines via a DLL.


Usage: dh = dencp(x,h,xest,loo,kernden)
Input:
ATTENTION: this quantlet requires to open locling.dll, density.dll (NT) or locling.so, denc.so (UNIX). This can be done with the quantlet cafpeload or directly with garb = dlopen ("\density.dll") on NT, garb = dlopen ("/denc.so") on UNIX.
x (n x d) matrix of observations
h (d x 1) vector of bandwidths
xest (nest x d) matrix of points at which the density has to be computed
loo scalar, parameter to control leave-one-out: 0 = no leave-one-out, 1 = leave-one-out
kernden character variable for selecting kernel function: "gaussian": Gaussian kernel
Output:
dh (nxest x 1) estimated density at xest

Example:
pathcafpe = "tp/cafpe/"
library("xplore")
func(pathcafpe + "cafpeload.xpl")
cafpeload(pathcafpe)
n               = 100
x               = normal(n,1)
loo     = 0
kerntype = "gaussian"
h               = hsilv(sqrt(var(x)),1,n,kerntype)
xs		= sort(x)
dh      = dencp(x,h,xs,loo,kerntype)
plotoneline(xs~dh, "density estimate", " ", " ")
Result:

Library: cafpe
See also: tp/cafpe/fvllc

Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Author: Tschernig 000420
(C) MD*TECH Method and Data Technologies, 27.4.2000