[R] Testing additive nonparametric model
Donal O'Neill
donal.oneill at nuim.ie
Tue Apr 3 18:38:58 CEST 2007
Dear Vito,
Thank you for your prompt reply. Perhaps I am missing something but as
I understand it the procedure you suggest would allow me to test for
nonlinearities in one of the control variables. However my objective
is to nonparametrically test whether the nature of the nonlinearity in
one variable is constant across all values of a second conditioning
variable. That is I want to test y=f(x1,x2)+e against y=f1(x1)+f2(x2)
+ u
I tried
library(mgcv)
mod.1<-gam(y~s(x1)+s(x2))
mod.2<-loess(y~x1+x2, f=**, iter=**), lwd=**)
anova(mod.1, mod.2)
but got the following error message
Error in s^2 : non-numeric argument to binary operator
Any suggestions would be welcome.
Donal.
At 11:43 03/04/2007 +0200, vito muggeo wrote:
You can use the LRT (although I think that it assumes the df to be
fixed). For instance the package mgcv by Simon Wood has an anova
method to compare models fitted by the relevant gam() function, and
the print.summary() itself returns such information..
best,
vito
set.seed(123)
n<-100
sig<-2
x0 <- runif(n, 0, 1)
x1 <- runif(n, 0, 1)
y <- sin(2*pi*x0) + .5*x1 +sig*rnorm(n)
library(mgcv)
obj<-gam(y~s(x0)+s(x1))
obj1<-gam(y~s(x0)+x1)
anova(obj1,obj,test="F")
#also see the "Approximate significance of smooth terms"
summary(obj)
Donal O'Neill wrote:
I have estimated a multiple nonparametric regression using the
loess command in R. I have also estimated an additive version of
the model using the gam function. Is there a way of using the
output of these two models to test the restrictions imposed by the
additive model?
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Vito M.R. Muggeo
Dip.to Sc Statist e Matem `Vianelli'
Università di Palermo
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90128 Palermo - ITALY
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