[R] It is possible to use "input parameters" with "standard error" in fitting function nls
bgunter.4567 at gmail.com
Wed Aug 3 18:41:43 CEST 2016
You have not received a reply. I think it is because your post appears
to reveal a profound lack of understanding about how empirical
modeling works: the uncertainty in parameter estimates derives from
the uncertainty in the data (via the modeling process, of course). You
cannot set them independently as "input."
I urge that you consult a local statistical expert, take a statistics
course or two, and/or do some studying before proceeding further.
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Wed, Aug 3, 2016 at 1:57 AM, Vicente Martí Centelles
<martiv at qio.uji.es> wrote:
> Dear all,
> I would like to introduce an input parameter with an associated standard
> error to perform a fitting using the nls function (or any similar function):
> parameter1 = 9.00 +/- 0.20 (parameter 1 has a value of 9.00 and standard
> error of 0.20)
> fittingResults <- nls(y ~ function(xdata, ydata, parameter1,
> fittingparameter),start=list(parameter1=9.00, fittingparameter=5.00))
> Does anyone know how to introduce the associated standard error of the
> parameter to the fitting function?
> Many thanks for your help,
> Best regards
> *Dr. Vicente Martí Centelles*
> *Postdoctoral Researcher (VALi+d Generalitat Valenciana, Spain)*
> *Universitat Jaume I*Departamento de Química Inorgánica y Orgánica
> Avda Sos Baynat s/n
> E-12071-Castellón (Spain)
> Tel.: +34 964728235
> Fax: +34 964728214
> e-mail: martiv at qio.uji.es
> *web page*: www.vmarti.es
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