On Wed, 2012-10-03 at 12:09 +0100, Simon Wood wrote: > If b is a fitted gam object... > plot(b,all.terms=TRUE) > --- see ?plot.gam Many thanks for your answer! But the problem is not as simple. My model has one te(), and two parametric interactions: two numeric variables whose effects are changing in two conditions -- of the categorical factor with two levels. (I tried s(numericA, by=factorA) with them, but that is just an overfitting, since curves are actually lines, and anova() between the simpler and more complex model does not support the later.) Also, the model has a random effect. Thus, my problem is that plot.gam() does not support this interaction, i.e., all.terms=TRUE is not handling it, but only the 1st order terms. So, I was thinking that I could build a gam-model without one numericA:factorA interaction, and than take gam's residuals to build simple lm() and to plot that particular effect. Then, the same for the second interaction numericB:factorA. Unfortunately, I am not sure that my thoughts would pass sanity check. Can you comment, please?
Many thanks again! Best, Petar > On 02/10/12 20:36, Petar Milin wrote: > > Hello! > > Can anyone give a tip how to plot parametric effects in an Generalized > > Additive Model, from mgcv package? > > > > Thanks, > > PM ______________________________________________ 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.