Fit my model to data in binned Poisson Likelihood

Dear experts,

I am trying to fit binned data with simulated background+signal. I have an analytical expression for the signal in each bin, which is a quadratic order polynomial of two parameters. Due to low statistics, I need to use Poisson likelihood and not gaussian pdf. I need to get the 95% C.L. of parameters using Profile Likelihood Ratio. I am new to Roofit and RooStats. Could you help how to go about it? I was going through the example macro given in ROOT: tutorials/roostats/rs_numberCountingCombination.C File Reference . However, I am not able to understand how to give the binned analytical expression for the signal events that I have. Could you please help?

Best regards,
Antara

I think @jonas can help you

A response to the query would be helpful…

Thanks.

May be @moneta also knows.

Hi,
If you want to fit your binned data with a model and then estimate the 95% confidence intervals of the parameter using the profile likelihood ratio, you would need to perform a binned likelihood fit.
You organize first your data as a RooDataHist object and the you can model the signal function using standard RooFit classes. An example is the basic tutorial rf102_dataimport.C.
Afterwards you can either estimate the confidence intervals directly using Minos, or use the RooStats ProfileLikelihoodCalculator, as shown in this RooStats tutorial. If you have questions, please let me know

Lorenzo