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: regxest lregxestp regestp

Quantlet: regxestp
Description: computes the Nadaraya-Watson estimator for multivariate regression.

Reference(s):

Usage: mh = regxestp(x {,h {,K} {,v} })
Input:
x n x (p+1), the data. In the first p columns the independent variables, in the last column the dependent variable.
h scalar, p x 1 or 1 x p, bandwidth. If not given, 20% of the range of x[,1:p] is used.
K string, kernel function on [-1,1] or Gaussian kernel "gau". If not given, the Quartic kernel "qua" 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 (p=1), length 30 (p=2) and length 8 (p=3) is used in case of p<4. When p>=4 then v is set to x.
Output:
mh n x (p+1) or m x (p+1) matrix, the first p columns contain the grid or the sorted x[,1:p], the second column contains the regression estimate on the values of the first p 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 = regxestp(x,2)               ; estimate function

mh = setmask(mh,"surface","blue")

plot(x,mh)                       ; surface plot                  

setgopt(plotdisplay,1,1,"title","ROTATE!")

Result:

The Nadaraya-Watson regression estimate (blue) using   

Quartic kernel and bandwidth h=2 and the data are

pictured.


Library: smoother
See also: regxest lregxestp regestp

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, 21.9.2000