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)) Xa <- model.matrix(~a-1) ## random main effects Xb <- model.matrix(~b-1) Xab <- model.matrix(~a:b-1) ## random interaction dat$y <- dat$y + Xa%*%rnorm(10)*.5 + Xb%*%rnorm(7)*.3 + Xab%*%rnorm(70)*.7 dat$a <- a;dat$b <- b mod <- gam(y ~ s(a, bs="re") + s(x2, k = 15), data = dat) When I run plot(mod) I can see the adjustments for the "a" factor, but I don't know which adjustment is associated with which factor. Is it possible to extract the information underlying this plot numerically? Thanks! Jan -- View this message in context: http://r.789695.n4.nabble.com/mgcv-Extract-random-effects-from-gam-model-tp4637415.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
