[R] Constrained non linear regression using ML

Gabor Grothendieck ggrothendieck at gmail.com
Wed Mar 17 14:22:07 CET 2010


Contact the maintainer regarding problems with the package.  Not sure
if this is acceptable but if you get it to run you could consider just
dropping the variables from your model that correspond to active
constraints.

Also try the maxLik package.  You will have to define the likelihood
yourself but it does support constraints.

On Wed, Mar 17, 2010 at 9:07 AM, Corrado <ct529 at york.ac.uk> wrote:
> Dear Gabor,
>
> 1) The constraints are active, at least from a formal point view.
> 3) I have tried several times to run betareg.fit on the data, and the only
> thing I can obtain is the very strange error:
>
> Error in dimnames(x) <- dn :  length of 'dimnames' [2] not equal to array
> extent
>
> The error is strange because, because the function dimnames is not called
> anywhere.
> Regards
>
> Gabor Grothendieck wrote:
>>
>> Try it anyways -- maybe none of your constraints are active.
>>
>> On Wed, Mar 17, 2010 at 6:01 AM, Corrado <ct529 at york.ac.uk> wrote:
>>
>>>
>>> Dear Gabor, dear R users,
>>>
>>> I had already read the betareg documentation. As far as I can understand
>>> from the help, it does not allow for constrained regression.
>>>
>>> Regards
>>>
>>>
>>> Gabor Grothendieck wrote:
>>>
>>>>
>>>> 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
>>>>>
>>>>> ______________________________________________
>>>>> R-help at 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.
>>>>>
>>>>>
>>>>>
>>>
>>> --
>>> 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
>>>
>>>
>>>
>
>
> --
> 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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