Hi Sergio,
based on my understanding ( see Wood Generalized Additive Model)
smoothing basis incorporates the intercept already, due to identifiable
issues. Therefore the intercept is always specified and you don't need
to specify. I guess that your m2 to model is simply not correct.
Hope it helps
Anna
Anna Freni Sterrantino
Department of Statistics
University of Bologna, Italy
via Belle Arti 41, 40124 BO.
________________________________
Da: SAEC
A: r-help@r-project.org
Inviato: Giovedě 11 Ottobre 2012 0:22
Oggetto: [R] GAM without intercept
Hi everybody,
I am trying to fit a GAM model without intercept using library mgcv.
However, the result has nothing to do with the observed data. In fact
the predicted points are far from the predicted points obtained from the
model with intercept. For example:
#First I generate some simulated data:
library(mgcv)
x<-seq(0,10,length=100)
y<-x^2+rnorm(100)
#then I fit a gam model with and without intercept
m1<-gam(y~s(x,k=10,bs='cs'))
m2<-gam(y~s(x,k=10,bs='cs')-1)
#and now I obtain predicted values for the interval 0-1
x1<-seq(0,10,0.1)
y1<-predict(m1,newdata=list(x=x1))
y2<-predict(m2,newdata=list(x=x1))
#plotting predicted values
plot(x,y,ylim=c(0,100))
lines(x1,y1,lwd=4,col='red')
lines(x1,y2,lwd=4,col='blue')
In this example you can see that the red line are the predicted points
from the model with intercept which fit pretty good to the data, but the
blue line (without intercept) is far from the observed points.
Probably I missunderstanding some key elements in gam modelling or using
incorrect syntaxis. I don't know what the problem is. Any ideas will be
helpful.
Sergio
--
Sergio A. Estay
Inst. Ciencias Ambientales y Evolutivas
Universidad Austral de Chile
Casilla 567, Valdivia, Chile
Phone: 5663-293913
http://www.ciencias.uach.cl/instituto/ciencias_ambientales_evolutivas/academicos/sergio-estay.php
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