[R] nls function

[Andrew Robinson]

Hi Bill,

I've just spent a few months trying to fit a model to a dataset, and it's not 
easy.  However, in my case, what appears to be recalcitrance on R's part 
actually turns out to be well-founded warnings that the structure of the 
model and the data are not permitting a clean, unambiguous fit.  

I warmly recommend the Bates and Watts book on non-linear regression analysis, 
and also Venables and Ripley MASS, with especial reference to the online 
complements.

My strategy to learn more about my problem was: increase "tol" and decrease 
minFactor until I get a fit, and then examine the intrinsic and parameter 
curvatures using the rms.curv() function in the MASS package.  It showed 
quite clearly that there was a real problem with the parameterization of the 
model.  Of course, using that particular fit was out of the question.

I recommend against trying another tool: instead, learn more about this one 
and why it's behaving in that way.  Good luck. 

Andrew

On Thursday 01 April 2004 07:37, Bill Shipley wrote:
> Hello.  I am trying to fit a non-rectangular hyperbola function to data
> of photosynthetic rate vs. light intensity.  There are 4 parameters that
> have to be estimated.  I find the nls function very difficult to use
> because it often fails to converge and then gives out cryptic error
> messages.  I have tried playing with the control parameters but this
> does not always help.
>
> Is there another non-linear regression function in R that I might try
> (other than regression smoothers, which won’t give the parameter
> estimates of the specified function)?
>
>
>
> Bill Shipley
>
> Subject Matter Editor, Ecology
>
> North American Editor, Annals of Botany
>
> Département de biologie, Université de Sherbrooke,
>
> Sherbrooke (Québec) J1K 2R1 CANADA
>
> Bill.Shipley at USherbrooke.ca
>
>  <http://callisto.si.usherb.ca:8080/bshipley/>
> http://callisto.si.usherb.ca:8080/bshipley/
>
>
>
>
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Andrew Robinson                      Ph: 208 885 7115
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