XploRe Help : regxest

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:	regxci regxcb regest regxbwsel lpregxest regxestp

Quantlet:		regxest
Description:		computes the Nadaraya-Watson estimator for univariate regression.

Reference(s):

Haerdle, W. (1990). Applied Nonparametric Regression. Econometric Society Monographs, No. 19. Cambridge University Press.

Usage:	`mh = regxest(x {,h {,K} {,v} })`
Input:
	`x`	n x 2 matrix, the data. The first column contains the independent and the second column the dependent variable.
	`h`	optional scalar, bandwidth. If not given, 20% of the range of x[,1] is used as default.
	`K`	optional string, kernel function on [-1,1] or Gaussian kernel "gau". If not given, the Quartic kernel "qua" is used as default.
	`v`	optional m x 1 vector, values of the independent variable on which to compute the regression. If not given, the (sorted) x is used as default.
Output:
	`mh`	n x 2 or m x 2 matrix, the first column represents the sorted first column of x or the sorted v and the second column contains the regression estimate on the values of the first column.

Note:

This function does an exact computation, i.e., requires O(n^2) operations for estimating the regression function on all observations. For exploratory purposes, the quantlet "regest" is recommended, which uses the faster WARPing method.

Example:

library("smoother") library("plot") ; x = 4.*pi.*(uniform(200)-0.5) ; independent variable m = cos(x) ; true function e = uniform(200)-0.5 ; error term x = x~(m+e) ; mh = regxest(x,1) ; estimate function ; mh = setmask(mh, "line","blue") m = setmask(sort(x[,1]~m) , "line","black","thin") plot(x,mh,m)

Result:

The Nadaraya-Watson regession estimate (blue line) using
Quartic kernel and bandwidth h = 1 and the true
regression function (thin black line) are pictured.

Example:

library("smoother") library("plot") ; x = read("motcyc") ; read motorcycle data mhe = regxest(x,3,"epa") ; estimate function mhu = regxest(x,2,"uni") ; estimate function ; mhe= setmask(mhe,"line","green") mhu= setmask(mhu,"line","red") plot(x,mhe,mhu) ; graph functions

Result:

The Nadaraya-Watson regession estimates using
Epanechnikov kernel (green line) and Uniform kernel
(red line) are pictured.

Author: M. Mueller, 20020915