Dear R users, I´ve stumbled over a problem that can be easily seen from the R code below:
- When I use plot.gam() on a fitted model object, I get a nice and well-looking smooth curve for all terms in the model. - However, when I use predict(model) for a given predictor, with values of all other predictors set to their means, the resulting curve doesn´t fit well at all. Is there a way to "overlay" the curve produced by plot.gam() over a plot of the original data? Here´s some reproducible code with mgcv version 1.7-22 on R3.0.1 (Windows 7): ## library(mgcv) set.seed(2) dat <- gamSim(1,n=400,dist="normal",scale=2) b <- gam(y~s(x0)+s(x1)+s(x2)+s(x3),data=dat) plot(b,select=1) plot(y~x0,dat) mydata=data.frame(x0=0:1,x1=mean(dat$x1),x2=mean(dat$x2),x3=mean(dat$x3)) lines(0:1,predict(b,mydata,type="response")) ## Best wishes, Christoph -- PD Dr Christoph Scherber Georg-August University Goettingen Department of Crop Science Agroecology Grisebachstrasse 6 D-37077 Goettingen Germany phone 0049 (0)551 39 8807 fax 0049 (0)551 39 8806 http://www.gwdg.de/~cscherb1 ______________________________________________ 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.
