I need to use this method for a function which I want to introduce.
I try with the fit panel, no chance for both cases, I cannot introduce the user function and when I select GSL + Levenberg-Marquardt method, and then click on fit, the process stays block so I have to re-boot.
Do you have an example of a script or a better description of how to use the FitPanel functionalities?
This will help me.
Thank y very much
Sor
To use this method you need to have first MathMore installed in the system.
You can check this by typing
root-config --has-mathmore
The answer must be yes
Then the method works hen you are doing a least-square (chi-square) fit, for example when fitting an histogram or a Graph.
From the command line you can select the method by doing before fitting
In the case of the FitPanel you can select in the Minimisation tab. It works for me, so if it is strange it is halting your system. You should try to use from a macro. In case please send me your fitting object and function (histogram or graph).
If you want to use the algorithm to minimise a user-defined least-square function, it is possible but in that case the least square function must implement the ROOT::Math::FitMethodFunction interface.
It is working, many thanks.
I have few more questions.
1)I am working on Windows 64 Entreprise 7.
Maybe is a silly question but how do i run the command
root-config --has-mathmore
Obviously the installation on Windows has it because
ROOT::Math::MinimizerOptions::SetDefaultMinimizer(“GSLMultiFit”); worked.
On MAC it is working from the terminal but on Windows I didn’t managed to make it run.
2)how can I make 100 times iteration and printout the results of the parameters.
Many thanks
Sor
Thanks it is working perfectly.
One more question, how can i see how was implemented the method, is the equation the “damped version”, and if so what is the default value?
Sor
If you want to know more about the algorithm, you can look at the reference given in the GSL documentation,
J.J. Moré, The Levenberg-Marquardt Algorithm: Implementation and Theory, Lecture Notes in Mathematics, v630 (1978), ed G. Watson.