Hi Patrick, there exist specialized functionality in R that offer both automated calculation of starting values and relatively robust optimization, which can be used with success in many common cases of nonlinear regression, also for your data:
library(drc) # on CRAN ## Fitting 3-parameter logistic model ## (slightly different parameterization from SSlogis()) bdd.m1 <- drm(pourcma~transat, weights=sqrt(nbfeces), data=bdd, fct=L.3()) plot(bdd.m1, broken=TRUE, conLevel=0.0001) summary(bdd.m1) Of course, standard errors are huge as the data do not really support this model (as already pointed out by other replies to this post). 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.
