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: smoother
See also: regxestp lpregxest lregestp

Macro: lregxestp
Description: estimates a multivariate regression function using local polynomial kernel regression with Quartic kernel.

Reference(s):

Usage: mh = lregxestp(x {,h {,K} {,v} })
Input:
x n x (k+1), the data. In the first p columns the independent variables, in the last column the dependent variable.
h scalar or k x 1 vector, bandwidth. If not given, 20% of the volume of x[,1:k] is used.
v m x p, values of the independent variable on which to compute the regression. If not given, a grid of length 100 (k=1), length 30 (k=2) and length 8 (k=3) is used in case of k<4. When k>=4 then v is set to x.
Output:
mh n x (k+1) or m x (k+1) matrix, the first k columns contain the grid or the sorted x[,1:k], the second column contains the regression estimate on the values of the first k columns.

Note:

Example:
library("smoother") 
library("plot")
;
x = 2.*pi.*(uniform(200,2)-0.5)  ; independent variable
m = sum(cos(x),2)                ; true function
e = uniform(200)-0.5             ; error term             
x = x~(m+e)                             
;
mh = lregxestp(x,2)              ; estimate function
mh = setmask(mh,"surface","blue")
plot(x,mh)                       ; surface plot                  
setgopt(plotdisplay,1,1,"title","ROTATE!")
Result:
The local linear regression estimate (blue) using   
Quartic kernel and bandwidth h=2 and the data are
pictured.

Library: smoother
See also: regxestp lpregxest lregestp

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: Marlene Mueller, 990413
(C) MD*TECH Method and Data Technologies, 17.8.2000