As an addendum to my question, I'm attempting to apply the solution to the robust non-linear regression function nlrob from the robustbase package, and it doesn't work in that situation. I'm getting
allRobustFit <- nlrob(Y ~ (upper)/(1+10^(X-LOGEC50[dset])), data=all ,start=list(upper=max(all$Y),LOGEC50=c(-8.5,-8.5,-8.5))) Error in nls(formula, data = data, start = start, algorithm = algorithm, : parameters without starting value in 'data': LOGEC50 I'm guessing this is because the nlrob function doesn't know what to do with a vector for a start value. Am I correct and is there another method of using nlrob in the same way? Thanks, Jared On Tue, Oct 12, 2010 at 8:58 AM, Jared Blashka <evilamaran...@gmail.com>wrote: > Thanks so much! It works great. > > I had thought the way to do it relied on combining the data sets, but I > couldn't figure out how to alter the formula to work with the combination. > > Jared > > > On Tue, Oct 12, 2010 at 7:07 AM, Keith Jewell <k.jew...@campden.co.uk>wrote: > >> >> "Jared Blashka" <evilamaran...@gmail.com> wrote in message >> news:aanlktinffmudugqnkudvr=fmf0wrrtsbjxjexuki_...@mail.gmail.com... >> > I'm working with 3 different data sets and applying this non-linear >> > regression formula to each of them. >> > >> > nls(Y ~ (upper)/(1+10^(X-LOGEC50)), data=std_no_outliers, >> > start=list(upper=max(std_no_outliers$Y),LOGEC50=-8.5)) >> > >> > Previously, all of the regressions were calculated in Prism, but I'd >> like >> > to >> > be able to automate the calculation process in a script, which is why >> I'm >> > trying to move to R. The issue I'm running into is that previously, in >> > Prism, I was able to calculate a shared value for a constraint so that >> all >> > three data sets shared the same value, but have other constraints >> > calculated >> > separately. So Prism would figure out what single value for the >> constraint >> > in question would work best across all three data sets. For my formula, >> > each >> > data set needs it's own LOGEC50 value, but the upper value should be the >> > same across the 3 sets. Is there a way to do this within R, or with a >> > package I'm not aware of, or will I need to write my own nls function to >> > work with multiple data sets, because I've got no idea where to start >> with >> > that. >> > >> > Thanks, >> > Jared >> > >> > [[alternative HTML version deleted]] >> > >> An approach which works for me (code below to illustrate principle, not >> tried...) >> >> 1) combine all three "data sets" into one dataframe with a column (e.g. >> dset) indicating data set (1, 2 or 3) >> >> 2) express your formula with upper as single valued and LOGEC50 as a >> vector >> inderxed by dest e.g. >> Y ~ upper/(1+10^(C-LOGEC50[dset])) >> >> 3) in the start list, make LOGEC50 a vector e.g. using -8.5 as start for >> all >> three LOGEC50 values >> start = >> list(start=list(upper=max(std_no_outliers$Y),LOGEC50=c(-8.5, -8.5, -8.5)) >> >> Hope that helps, >> >> Keith J >> >> ______________________________________________ >> 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. >> > > [[alternative HTML version deleted]] ______________________________________________ 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.
