Hi all,
I hope that there might be some statistician out there to help me for a
possible explanation for the following simple question.
Y1~ lm(y~ t1 + t2 + t3 + t4 + t5,data=temp) # oridnary linear model
library(gam)
Y2~ gam(y~ lo(t1) +lo(t2) +lo(t3) +lo(t4) +lo(t5),data=temp) # additive
model
In the first model t1, t2 and t3 found to be significant,.
However, in the second model (using gam package) t1, t4 and t5 are
significant.
I was hopping to expect nearly similar results from both models but I found
the opposite results.
Is there any possible explanation for that?
Thanks
Val
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
