# [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
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--
====================================
Vito M.R. Muggeo
Dip.to Sc Statist e Matem `Vianelli'
Università di Palermo
viale delle Scienze, edificio 13
90128 Palermo - ITALY
tel: 091 6626240
fax: 091 485726/485612
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References

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