Check out the betareg package. On Tue, Mar 16, 2010 at 2:58 PM, Corrado <ct...@york.ac.uk> wrote: > Dear R users, > > I have to fit the non linear regression: > > y~1-exp(-(k0+k1*p1+k2*p2+ .... +kn*pn)) > > where ki>=0 for each i in [1 .... n] and pi are on R+. > > I am using, at the moment, nls, but I would rather use a Maximum Likelhood > based algorithm. The error is not necessarily normally distributed. > > y is approximately beta distributed, and the volume of data is medium to > large (the y,pi may have ~ 40,000 elements). > > I have studied the packages in the task views Optimisation and Robust > Statistical Methods, but I did look like what I was looking for was there. > Maybe I am wrong. > > The nearest thing was nlrob, but even that does not allow for constraints, > as far as I can understand. > > Any suggestion? > > Regards > > -- > Corrado Topi > PhD Researcher > Global Climate Change and Biodiversity > Area 18,Department of Biology > University of York, York, YO10 5YW, UK > Phone: + 44 (0) 1904 328645, E-mail: ct...@york.ac.uk > > ______________________________________________ > 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. >
______________________________________________ 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.
