Dear Christoph, using the package 'alr3' it's not difficult!
Have a look at the following example: ## Fitting a Michaelis-Menten model Puromycin.m1<-nls(rate~a*conc/(b+conc), data=Puromycin[1:12,], start=list(a=200, b=1)) library(alr3) ## Predictions (with standard errors) at concentrations 0.02, 0.06, and 011 delta.method(Puromycin.m1, "a*0.02/(b+0.02)") delta.method(Puromycin.m1, "a*0.06/(b+0.06)") delta.method(Puromycin.m1, "a*0.11/(b+0.11)") Hope you can make it work for your own application! Christian ______________________________________________ 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.
