Re: [R] mgcv 1.7-19, vis.gam(): "invalid 'z' limits'

I somehow solved the problem - kind of. The data set on which I ran the GAM model contains many more variables than are needed in the model, so I created a new data set in R and reran the GAM model on the slimmed down data set. Same problem: The GAM can be computed, but the tensor product cannot be

Re: [R] mgcv 1.7-19, vis.gam(): "invalid 'z' limits'

Hi Simon, Thanks for your reply. m <- bam(Correct ~ cEnglishTotal + te(WSTResid, RavenResid) + s(Stimulus, bs="re") + s(Subject, bs="re"), data = dat, family = "binomial") # cEnglishTotal, WSTResid and RavenResid are continuous variables; Correct, Stimulus and Subject are factors. > vis.gam(m, v

[R] mgcv 1.7-19, vis.gam(): "invalid 'z' limits'

Hi everyone, I ran a binomial GAM consisting of a tensor product of two continuous variables, a continuous parametric term and crossed random intercepts on a data set with 13,042 rows. When trying to plot the tensor product with vis.gam(), I get the following error message: Error in persp.default

[R] mgcv: Extract random effects from gam model

Hi everyone, I can't figure out how to extract by-factor random effect adjustments from a gam model (mgcv package). Example (from ?gam.vcomp): library(mgcv) set.seed(3) dat <- gamSim(1,n=400,dist="normal",scale=2) a <- factor(sample(1:10,400,replace=TRUE)) b <- factor(sample(1:7,400,replace=TRUE)