Hello!
I am running R-2.3.1-i386-1 on Slackware Linux 10.2. I am a former matlab user,
moving to R. In matlab, via the cftool, I performed nonlinear curve fitting
using the method "nonlinear least squares" with the
"Trust-Region" algorithm and not using robust fitting. Is it possible
to perform the same analysis in R? I read quite a lot of R documentation, but I
could not find an alternative solution. If there is such, please forgive my
ignorance (I am a newbie in R) and tell me which function from which package is
capable of performing the same analysis. If the same analysis is not possible to
carry out in R, I would be grateful if you suggest to me some alternative
procedure. I found that the "nls" function performs nonlinear least
squares. The problem is that I do not want to implement the Gauss-Newton
algorithm. In the worst case I would be contented with the
"Levenberg-Marquardt" algorithm, if it is implemented in R. R
nls's documentation mentions the "port" package and the
?nl2sol? algorithm, but I could not find that package in the CRAN repository,
so that I could read and judge whether that algorithm would be appropriate.
Thank you very much in advance. I am looking forward to your answer.
Regards,
Martin
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