hello, I am looking for a step() function for GAM's. In the book Statistical Computing by Crawley and a removal of predictors has been done "by hand"
model <- gam(y ~s(x1) +s(x2) + s(x3)) summary(model) model2 <- gam(y ~s(x2) + s(x3)) # removal of the unsignificant variable #then comparing these two models if an significant increase occurs. anova(model, model2, test="F") isn't there a way to drop and add variables automatically until the best model is received? like in step(lm(...))? Or as in grasp.step.gam() - but that doesn't work when I tried it outside GRASP-R. thanks for your help, cheers Martin ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
