Re: [R] MGCV: overlay fitted (marginal) curves over a plot of the original data

Meanwhile, I found the solution myself: using plot.gam() with shift=intercept and trans=exp (for a poisson model) does the job. I can then add the original data using points() Thanks again for your help, which is greatly appreciated! Best wishes Christoph Am 16/07/2013 11:04, schrieb Simon Woo

Re: [R] MGCV: overlay fitted (marginal) curves over a plot of the original data

Thanks, the sequence of x0 values was clearly too short. However, is there a way to overlay the (marginal) curve from plot.gam() over a plot of (x,y) values? Best wishes Christoph Am 16/07/2013 11:04, schrieb Simon Wood: > Probably you didn't want to set x0=0:1? Here is some code, to do what

Re: [R] MGCV: overlay fitted (marginal) curves over a plot of the original data

Probably you didn't want to set x0=0:1? Here is some code, to do what you want. (The CI shape is not identical to the plot(b) version as the uncertainty includes the uncertainty in the other smooths and the intercept now.) library(mgcv) set.seed(2) dat <- gamSim(1,n=400,dist="normal",scale=2) b

[R] MGCV: overlay fitted (marginal) curves over a plot of the original data

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 othe