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Difference between extended maximum likelihood and maximum likelihood method

Dear Expert,

I want to understand the difference between the extended maximum likelihood and maximum likelihood method. I am looking into the example ROOT: tutorials/roofit/rf307_fullpereventerrors.C File Reference. Here This is not the extended maximum likelihood fit.
Can you please tell me the reason behind this?

Regards
Chanchal

Hi,

I think this old paper from R. Barlow defines the extended ML:

https://doi.org/10.1016/0168-9002(90)91334-8

Lorenzo

thankyou for this paper

Hi,

extended likelihood is when you assign Poisson distribution to coefficients in the sum of pdfs. The original paper is cited above, but today I read a clear and consise explanation in the presentation of Craig Blocker, pages 14 and 15. Hope this helps.

Hii,

Thank you, it’s really very helpful.

Regards
Chanchal

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