[R] Constrained non linear regression using ML

[Gabor Grothendieck]

Check out the betareg package.

On Tue, Mar 16, 2010 at 2:58 PM, Corrado <ct529 at 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: ct529 at york.ac.uk
>
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