R help - May 2000 - Non linear regression using Levenberg-Marquardt method

Hello,

I want to fit some non linear models with the Levenberg-Marquardt
algorithm. It doesn''t seem to exist any function to do this in R (
well,
maybe one does, but I''m a new user, and the only documentation I have
is
"An introduction to R").
I''d like to know if this function exists, maybe throught an additionnal
package.

I''d also like to know if if I can fit my models without giving initial
estimates of the parameters. The problem is that I have to fit four non
linear models with a lots of data sets, so I can''t plot the data and
guess parameters values for each of them.

Thanks for all

Marjorie
-- 
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BOURGOIN Marjorie
CEA Saclay
Departement d''Ingenierie et d''Etude des Proteines
Bat. 152
91191 GIF sur YVETTE
FRANCE
Tel:01-69-08-71-35 
mbourgoi at salome.saclay.cea.fr        
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On Mon, 15 May 2000, Marjorie Bourgoin wrote:
> Hello,
> 
> I want to fit some non linear models with the Levenberg-Marquardt
> algorithm. It doesn''t seem to exist any function to do this in R (
well,
> maybe one does, but I''m a new user, and the only documentation I
have is
> "An introduction to R").
> I''d like to know if this function exists, maybe throught an
additionnal
> package.
The nls package fits many non-linear models. Some of them are
''self-starting''; they don''t need starting values. 
Even if your model
isn''t one of them you might be able to work out how to make it
self-starting.

I don''t think it uses a Levenberg-Marquardt algorithm, but that
shouldn''t
matter.

You could also code the model as a minimisation problem and feed it to
optim(), which also doesn''t use a Levenberg-Marquardt model.


	-thomas

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