# Re: [R] Curve fitting

From: Albyn Jones <jones_at_reed.edu>
Date: Fri 13 Jan 2006 - 06:54:38 EST

You haven't told us how you are fitting the model; are you using nls(), and if so with what initial values? The models don't make sense at x=0, due to the inclusion of the log(x) term. Ignoring that, you have 5 observations and 5 parameters in your second model. What is the reason you are including both "b*log(x)" and "c*x" terms in the model?

regards

albyn

On Thu, Jan 12, 2006 at 07:11:12PM +0100, ndurand@fr.abx.fr wrote:
> Hi!
>
> I have a problem of curve fitting.
>
> I use the following data :
>
> - vector of predictor data :
> 0
> 0.4
> 0.8
> 1.2
> 1.6
>
> - vector of response data :
> 0.81954
> 0.64592
> 0.51247
> 0.42831
> 0.35371
>
> I perform parametric fits using custom equations
>
> when I use this equation : y = yo + K *(1/(1+exp(-(a+b*ln(x))))) the
> fitting result is OK
> but when I use this more general equation : y = yo + K
> *(1/(1+exp(-(a+b*log(x)+c*x)))) , then I get an aberrant curve!
>
> I don't understand that... The second fitting should be at least as good
> as the first one because when taking c=0, both equations are identical!
>
> There is here a mathematical phenomenon that I don't understand!....could
> someone help me????
>
> Thanks a lot in advance!
>
>
> [[alternative HTML version deleted]]
>

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R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Fri Jan 13 07:06:07 2006

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