[R] non linear modelling with nls: starting values

[Sebastian P. Luque]

On 18 Sep 2006 17:55:24 +0200,
Peter Dalgaard <p.dalgaard at biostat.ku.dk> wrote:

> "Gabor Grothendieck" <ggrothendieck at gmail.com> writes:
>> Here are some approaches:

>> - we only have 4 parameters so just use grid search to get starting
>> values as in:

>> https://stat.ethz.ch/pipermail/r-help/2005-September/079617.html

>> - there are singularities near beta_1 = beta_2 and near alpha_1 = 0 and
>> near alpha_2 = 0 so reparameterize and use the upper and lower bounds
>> to avoid those regions.  You could try a separate reduced model for
>> those.


> Or just use SSbiexp and reparametrize (it is exactly the same model)

Thank you Gabor and Peter.  With your help, I was able to fit the model
using SSbiexp as Peter suggested.  However, the dependent variable spans
both negative and positive values, and the negative values cause the
fitting procedure to fail with a NA/NaN/Inf error.  This might be related
to the singularities that Gabor mentioned.  If the dependent variable is
shifted upwards, so all values are positive, the model is fit without
problems.  Any ideas on how to get around this issue without shifting the
data, so that the parameters are expressed in the original scale?
Hopefully it's possible to do it using SSbiexp.  Thanks again.


Cheers,

-- 
Seb