Library: | plm |
See also: | plmk plmlorg |
Quantlet: | plmp | |
Description: | plmp estimates the parametric part in partially linear models by using piecewise polynomial to approximate the nonparametric part |
Usage: | res = plmp(x,t,y,m,mn) | |
Input: | ||
x | n x p matrix, the design | |
t | n x 1 matrix, the design in [0, 1] | |
y | n x 1 matrix, the response | |
m | scalar, degree of piecewise polynomial | |
mn | scalar, the numbers of intervals divided [0, 1] with length 1/mn. | |
Output: | ||
res.hbeta | p x 1 matrix, the estimate of the parameter | |
res.hg | n x 1 matrix, estimate of nonparameter function |
library("plm") n = 100 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) m =2 mn=5 res=plmp(x,t,y,m,mn) ddp=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(ddp,1,1,datah1,datah2) setgopt(ddp,1,1,"xlabel","T","title","Simulation comparison","ylabel","g(T) and its estimate values")
The parameter estimates, see Hung Chen "Convergence Rates for Parametric Components in A Partly Liner Model", Ann. of Statist. (1988) 16, 136-146.