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Advanced usage of TLinearFitter?

Hi,
I’m using TLinearFitter in order to fit datasets in a 3-dim space. I’m using a polynom up to grade 2.

I have a few questions:

  1. I’m trying to illustrate the results by fixing two variables of the fit and make several TF1 out of the 3-dim fit. Is there a common method to do this. Currently, I’m calculating the results manually by using GetParameters(). What I’m searching for is

TF1 * TLinearFitter:GetTF1(int fixed par, Double_t p1, Double_t p2, Double_t p3,…) // The entry of the fixed parameter is regardless

  1. Why isn’t there an Double_t TLinearFitter::Evaluate (Double_t p1, Double_t p2, Double_t p3, …) Function, as it is known from TF1??

  2. Is there an easy method to access the confidence level of the fit (in dependency of the parameters? I would like to make a 1d representation (see question 1) including the error limits

  3. How do I access the R^2 (Representing the fit-quality). Usually R^2 (always smaller than 1, but close to 1 means good fit)

Thanks
Georg


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Hi @Georg_T,
and sorry for the late reply!

We need @moneta’s help on this one, let’s ping him.

Cheers,
Enrico

I guess you would like a profiled function, i.e. a TF1 that is a function of the fixed parameter and the TLinearFitter finds the minimum value for the other two.
There is not such function available, but one can implement this, for example using a lambda or a functor that deals with create the lines fritter, fixing the parameter value and find the solution.

Why this should evaluate ? To the chisquare function given the parameter values ?
For this you can call TLinearFitter::GetChisquare().

No, you can compute confidence intervals on the parameters as is done in Minos (see point 1) or otherwise why not running Migrad+Minos after the linear fitter ?

I don’t know what is R^2.

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