Note that your post has no subject line. I can't find it in my emails, which may explain why no one else has replied.
> fo<-h~a+b*log(dbh)+c*(log(dbh))^2+1.3 I'm assuming that you want to fit a model with three parameters, a, b and c. This would be a linear model (linear in the parameters). I'm going to ignore the +1.3 (because you don't need two intercepts), but you can modify the following script if you want. > I want to compute a nlm for each plot So, three models? How about this: > r1 = lm (h ~ log (dbh) + I ( (log (dbh) ) ^ 2), data=ah > [ah$plot=="Sinca",])$coef > r2 = lm (h ~ log (dbh) + I ( (log (dbh) ) ^ 2), data=ah > [ah$plot=="budeni",])$coef > r3 = lm (h ~ log (dbh) + I ( (log (dbh) ) ^ 2), data=ah > [ah$plot=="Ceahlau",])$coef > params = rbind (r1, r2, r3) > rownames (params) = c ("Sinca", "budeni", "Ceahlau") > colnames (params) = c ("a", "b", "c") > params a b c Sinca -13.05110 5.657927 1.606357 budeni -2.11277 3.997636 1.104683 Ceahlau -135.57911 82.836952 -10.918932 ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.