XploRe Help : plmls

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:	plm
See also:	plmk plmp

Quantlet:		plmls
Description:		plmls estimates partially linear models by using least squares spline to approximate the nonparametric part.

Usage:	`res = plmls(x,t,y,m,knots)`
Input:
	`x`	n x p matrix, the design points
	`t`	n x 1 matrix, the design ponits
	`y`	n x 1 matrix, the response variables
	`m`	the order of spline
	`knots`	k x 1 matrix, knot sequence knots
Output:
	`res.hbeta`	p x 1 matrix, the estimate of the parameter
	`res.hg`	n x 1 matrix, the estimate of the nonparametric part

Example:

library("plm") proc()=main() n = 100 m=2 sig=0*matrix(3,3) sig[,1]=#(0.81,0.1,0.2) sig[,2]=#(0.1,2.25,0.1) sig[,3]=#(0.2,0.1,1) x =normal(n,3)*sig t =sort(uniform(n)) beta0=#(1.2, 1.3, 1.4) y =x*beta0+t^3+0.01*normal(n) kk=floor(rows(t)/2) knots=0*(1:kk) j=1 while(j<=kk) knots[j]=t[2*j] j=j+1 endo res=plmls(x,t,y,m,knots) ddls=createdisplay(1,1) datah1=t~t^3 datah2=t~res.hg part=grid(1,1,rows(t))' setmaskp(datah1,1,0,1) setmaskp(datah2,4,0,3) setmaskl(datah1,part,1,1,1) setmaskl(datah2,part,4,1,3) show(ddls,1,1,datah1,datah2) setgopt(ddls,1,1,"xlabel","T","title","Simulation comparison","ylabel","g(T) and its estimate values") endp main()

Result:

The parameter estimates, 3 x 1 matrix and nonparametric
fitting are presented.

Author: H. Liang, W. Haerdle, 19980512 license MD*Tech