Thank you all for your useful suggestions.
Jean, I had already tried to use the maxiter command in that way, but it simply
told me that the model had not converged.
Based on Profs Ripley and Nash's comments, I have opted to use an alternative
approach, and am creating a distribution of
Hi all,
I am attempting to apply a nonlinear model developed using nls to a new dataset
and assess the fit of that model. At the moment, I am using the fitted model
from my fit dataset as the starting point for an nls fit for my test dataset
(see below). I would like to be able to view the
Rebecca,
I'm not sure why you are interested in the t-statistics and p-values for
the iterations, but you could perhaps save the nls() fit after 1, 2, 3, ...
iterations using the argument nls.control(maxiter = n).
Jean
On Fri, Apr 5, 2013 at 12:06 AM, Rebecca Lester
On 05/04/2013 14:26, Adams, Jean wrote:
Rebecca,
I'm not sure why you are interested in the t-statistics and p-values for
the iterations, but you could perhaps save the nls() fit after 1, 2, 3, ...
iterations using the argument nls.control(maxiter = n).
But those statistics are only even
Given nls has a lot of C code (and is pretty complicated), I doubt
you'll find much joy doing that.
nlxb from my nlmrt package is all in R, but you'll need to do quite a
bit of work at each stage. I don't form the J' J matrix, and do a
Marquardt approximation by adding appropriate rows to the
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