Dear Bert Thanks for getting back to me. Yes that is exactly the sort of problem I am trying to solve. I am aware of the option of hard coding the experimental groups as you suggested, but was hoping for an easy out of the box approach as I have many groups! Thanks James
On Tue, 5 Nov 2019 at 20:28, Bert Gunter <bgunter.4...@gmail.com> wrote: > A simplified example of what you wish to do might help to clarify here. > > Here's my guess. Feel free to dismiss if I'm off base. > > Suppose your model is: > y = exp(a*x) + b > > and you wish the b to be constant but the a to vary across expts. Then can > you not combine the data from both into single x, y vectors, add a variable > expt that takes the value 1 for expt1 and 2 for expt 2 and fit the single > model: > > y = (expt ==1)*(exp(a1*x) + b) + (expt == 2)* (exp(a2*x) + b) > > This would obtain separate estimates of a1 and a2 but a single estimate of > b . > > There are probably better ways to do this, but I've done hardly any > nonlinear model fitting (so warning!) and can only offer this brute force > approach; so wait for someone to suggest something better before trying it. > > Cheers, > Bert > > > On Tue, Nov 5, 2019 at 9:12 AM James Wagstaff <wagstaff.ja...@gmail.com> > wrote: > >> Hello >> I am trying to determine least-squares estimates of the parameters of a >> nonlinear model, where I expect some parameters to remain constant across >> experiments, and for others to vary. I believe this is typically referred >> to as global curve fitting, or the presence of shared/nested parameters. >> The "[]" syntax in the stats::nls() function is an extremely convenient >> solution ( >> >> https://r.789695.n4.nabble.com/How-to-do-global-curve-fitting-in-R-td4712052.html >> ), >> but in my case I seem to need the Levenberg-Marquardt/Marquardt solvers >> such as nlsr::nlxb() and minpack.lm::nlsLM. I can not find any >> examples/documentation explaining a similar syntax for these tools. Is >> anyone aware of a nls-like tool with this functionality, or an alternative >> approach? >> Best wishes >> James Wagstaff >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> 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. >> > -- James Wagstaff +447910113349 [[alternative HTML version deleted]] ______________________________________________ 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.
