[R] Error "singular gradient matrix at initial parameter

[Gabor Grothendieck]

What do you mean the problem still stays?   If you are using brute
force its not a problem to have it fail on some of the evaluations
since each one is separate.  How large a grid are you using?  Are you
claiming that every single point on the grid fails? Please provide
reproducible code showing what you are doing.

On Tue, Mar 30, 2010 at 10:56 AM, Corrado <ct529 at york.ac.uk> wrote:
> Yes, of course. The problem still stays.
>
> Gabor Grothendieck wrote:
>>
>> Sorry, its algorithm="brute-force"
>>
>> On Tue, Mar 30, 2010 at 10:29 AM, Corrado <ct529 at york.ac.uk> wrote:
>>
>>>
>>> Hi Gabor,
>>>
>>> same problem even using nls2 with method=brute-force to calculate the
>>> initial parameters.
>>>
>>> Best,
>>>
>>> Gabor Grothendieck wrote:
>>>
>>>>
>>>> You could try method="brute-force" in the nls2 package to find starting
>>>> values.
>>>>
>>>> On Tue, Mar 30, 2010 at 7:03 AM, Corrado <ct529 at york.ac.uk> wrote:
>>>>
>>>>
>>>>>
>>>>> I am using nls to fit a non linear function to some data.
>>>>>
>>>>> The non linear function is:
>>>>>
>>>>> y= 1- exp(-(k0+k1*p1+ .... + kn*pn))
>>>>>
>>>>> I have chosen algorithm "port", with lower boundary is 0 for all of the
>>>>> ki
>>>>> parameters, and I have tried many start values for the parameters ki
>>>>> (including generating them at random).
>>>>>
>>>>> If I fit the non linear function to the same data using an external
>>>>> algorithm, it fits perfectly and finds the parameters.
>>>>>
>>>>> As soon as I come to my R installation (2.10.1 on Kubuntu Linux 910 64
>>>>> bit),
>>>>> I keep getting the error:
>>>>>
>>>>> Error in nlsModel(formula, mf, start, wts, upper) :   singular gradient
>>>>> matrix at initial parameter estimates
>>>>>
>>>>> I have read all the previous postings and the documentation, but to no
>>>>> avail: the error is there to stay. I am sure the problem is with nls,
>>>>> because the external fitting algorithm perfectly fits it in less than a
>>>>> second. Also, if my n is 4, then the nls works perfectly (but that
>>>>> excludes
>>>>> all the k5 .... kn).
>>>>>
>>>>> Can anyone help me with suggestions? Thanks in advance.
>>>>>
>>>>> Alternatively, what do you suggest I should do? Shall I abandon nls in
>>>>> favour of optim?
>>>>>
>>>>> 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
>
>