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: kernel
See also: highgau

Macro: highepa
Description: highepa computes the multivariate higher order kernel derived from the epanechnikov kernel

Usage: y = highepa(x, {q})
Input:
x n x p matrix
{q} order of the kernel, default is 2, can be 4, 6, 8
Output:
y n x 1 matrix

Example:
library("kernel") 
x = aseq(-1, 41, 0.05) 
y = highepa(x,6) 
t=createdisplay(1,1)                                      
show(t,1,1,x~y)                                    
Result:
The kernel is pictured  

Library: kernel
See also: highgau

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: Lijian Yang, 970719
(C) MD*TECH Method and Data Technologies, 28.6.1999