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: plmhett plmhetmean

Quantlet: plmhetexog
Description: plmhetexog estimates the parameter part in partially linear heteroscedastic models, in which the variance is an unknown function of exogenous variables

Usage: res = plmhetexog(x,t,y,w,h,{h1})
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
w n x 1 matrix, the response
h p x 1 matrix or scalar, chosen bandwidth
h1 scalar, chosen bandwidth
Output:
res.hbetals p x 1 matrix, LS estimate of parameter
res.hbeta p x 1 matrix, the estimate based on our method
res.hg0 n x 1 matrix, estimate of nonparameter function based on res.hbetals
res.hg n x 1 matrix, estimate of nonparameter function based on res.hbeta

Example:

library("plm")

randomize(100)

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))

w =sort(uniform(n)^3)

beta0=#(1.2, 1.3, 1.4)  ; the true value

y =x*beta0+t^3+0.1*(w+5/(1+w)).*normal(n)

h =0.15

res=plmhetexog(x,t,y,w,h)

res

ddp=createdisplay(1,1)

datah1=t~t^3

datah2=t~res.hg0

datah3=t~res.hg 

part=grid(1,1,rows(t))'

setmaskp(datah1,1,0,1)

setmaskp(datah2,4,0,3)

setmaskp(datah3,7,0,5)

setmaskl(datah1,part,1,1,1)

setmaskl(datah2,part,4,1,3)

setmaskl(datah3,part,2,1,1)

show(ddp,1,1,datah1,datah2,datah3)

setgopt(ddp,1,1,"xlabel","T","title","Simulation comparison","ylabel","g(T) and its estimate values")

Result:

The parameter estimates, see Hua Liang and Wolfgang

Haerdle" Asymptotic normality of parametric regression part in

partial linear heteroscedastic regression models",

DP 970033 of SFB 373.


Library: plm
See also: plmhett plmhetmean

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: Hua Liang, 12.05.1998
(C) MD*TECH Method and Data Technologies, 21.9.2000