[R] Curve fitting

[Albyn Jones]

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
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On Thu, Jan 12, 2006 at 07:11:12PM +0100, ndurand at 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!
> 
> Nad?ge 
> 
> 	[[alternative HTML version deleted]]
> 

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