I’m still new to the ROOT::FIT classes. In some of the fits, several parameters are kept fix; but they have an associated error.
In order to propagate these errors (associated with the fix parameters) to the “free” parameters, I have to perform several fits changing the values of the fixed parameters (a Montecarlo way of propagating errors).
So, my question is: is there a way using ROOT::FIT to propagate the errors of the fixed parameters?
I spent a while looking for it, but I didn’t find anything. So, in case of a negative answer, is there any more stylish way of propagating the errors? (I can provide a “simplified working code” if needed).
The correct way to include the uncertainty on those parameter is to include an additional term in the likelihood, such as a Gaussian constraint.
This is not foreseen actually in ROOT::Fit, but it is not complicated to do it by extending the negative log-likelihood with a quadratic term in the parameter (the log of a gaussian) and then use the ROOT::Fitter::FitFCN function to perform the fit.
If you need I could make an example for you