Fitting To Regions in RooFit

Hi all,
I am having some problems doing unbinned ML Fit in regions. I have data in range [70,120] of which [86,96] is my blind region (“blind”) and both side of it are the sidebands ("unblindReg_1 , unblindReg_2). The integral of data in [70,120] is 2637 ( blind: 614 and sidebands:2023). I am using a power law as my model(RooGenericPdf). I need to fit my model in the side bands → extract the parameter value (p) → Find normalisation in blind region from the model with parameter value p.

1.First I fit the model to data sideband regions without any extended normalisation going into the fit. The fit looks fine.
2. Take a model with parameter value same as obtained from step1 and extend it with a norm parameter → fitTo data in blind region → obtain the normalisation. Here the normalisation is coming out to be 3115 , even greater than integral of data in entire range!

I have attached the plots and the code snippet. It would be really helpful to know what i am missing here or is there a better way to do what i am trying to do.

###Step1: Fiting in sidebands without an extended norm.
p = r.RooRealVar(“p”,“p”,-1,-5,0)
data_bkg = r.RooGenericPdf(“data_bkg”,“data_bkg”,“Hm^p”,r.RooArgList(Hm,p))
fitresult = data_bkg.fitTo(data_obs,r.RooFit.Range(“unblindReg_1,unblindReg_2”),r.RooFit.Save())

###Step2:Fiting in blind region with parameter from side band fits with an extended norm.
p = r.RooRealVar(“p”,“p”,-3.1562)
data_bkg2 = r.RooGenericPdf(“data_bkg2”,“data_bkg2”,“Hm^p”,r.RooArgList(Hm,p))
blind_norm = r.RooRealVar(“blind_norm”,“blind_norm”,500,0,3500)
fitresult = data_bkg2_.fitTo(data_obs,r.RooFit.Range(“blind”),r.RooFit.Save())


Hi @sweta,

If you create a RooAddPdf, it’s coefficients/yields are still interpreted as applying to the full range, even if you only fit a subrange.

In the documentation to RooAbsPdf::fitTo(), you will see an option called SumCoefRange(). If you set this to your “blind” range, you should get the expected result.

Hope that works!

1 Like

Hi @jonas
Thanks. It worked for the blind range. I further tried using this on the sidebands by extending the sideband model of step1

##Fiting in sidebands with an extended norm.
p= r.RooRealVar(“p”,“p”,-1,-5,0)
data_bkg1 = r.RooGenericPdf(“data_bkg1”,“data_bkg1”,“Hm^p”,r.RooArgList(Hm,p))
side_norm = r.RooRealVar(“side_norm”,“side_norm”,500,0,3000)
fitresult = data_bkg1_.fitTo(data_obs,r.RooFit.Range(“unblindReg_1,unblindReg_2”),r.RooFit.SumCoefRange(“unblindReg_1,unblindReg_2”),r.RooFit.Save())

Here again the normalisation coefficient comes greater than expected if i dont put the ‘SumCoefRange(…)’ in the fitTo and it comes out to be smaller than expected when i include ‘r.RooFit.SumCoefRange(“unblindReg_1,unblindReg_2”)’ in the fit.
Is it that the 'SumCoefRange() works for a single range? If so how to extract normalisation coeff from fit in sidebands or in general multiple ranges?

Thanks again,

This topic was automatically closed 14 days after the last reply. New replies are no longer allowed.