I would like to perform a maximum likelihood fit (assuming Poisson statistics) of count histograms with variable bin width. Calling Sumw2, and using Scale(1., “width”) to normalize the content of each bin to the bin’s width, I get correct results when performing a chi2 fit - provided that the fit option “I” is used. However, for maximum likelihood fits I have not yet been successful, neither with Root versions 5.30 or 5.34. Is there a combination of fit options that would make Root take into account correctly the actual number of counts in each bin and at the same time use the “I” option in combination with fit options “L” or “WL”? During the fit, the actual number of counts could be derived from the known bin content and the bin width. However, in my attempts so far, my impression was that instead of the actual number of counts in each bin the bin content after normalization to the bin width is used.
Thank you very much for any advice,