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 ?nl 2sol? 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 ----------------------------------------------------------------- http://ide.li/ - ?????? ?? ????????? ?? ?????. ??????, ??????, ??????, ??????, ??????????.
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 ?nl 2sol? 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 ----------------------------------------------------------------- http://ide.li/ - ?????? ?? ????????? ?? ?????. ??????, ??????, ??????, ??????, ??????????.
1. "Port" is NOT and R package but something more generally
available. I just got 189 hits from Google for "nl2sol Port package",
some of which should answer your questions about that.
2. Have you considered 'nlminb' and 'optim'? There is
also a
"sequential quadratic programming" algorithm embedded in the code for
'garchFit{fSeries}'.
3. If you'd like more help from this listserve, please post
another question. When you do so, please provide commented, minimal,
self-contained, reproducible code, as suggested in the posting guide
"www.R-project.org/posting-guide.html". Please also help us
understand
why you don't want Gauss-Newton -- in prose as simple and clear as
possible. Doing so will increase your chances of a prompt reply that
will likely be closer to what you want.
Hope this helps.
Spencer Graves
Martin Ivanov wrote:> 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 ?nl
> 2sol? 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
>
> -----------------------------------------------------------------
> http://ide.li/ - ?????? ?? ????????? ?? ?????. ??????, ??????, ??????,
??????, ??????????.
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
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> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>