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Hello, I want to use pyhf to re-interpret an unfolded measurement. Unlike detector-level data, unfolded measurements in a given bin may have stat errors which are difference from the typical Poisson(n). Indeed, there can be significant correlations between bins even for stat uncertainties! So my question is twofold: best wishes and thanks for any advice! Louie |
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Replies: 1 comment 3 replies
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Sorry for not responding faster... this fell through. a) Extra uncertainties on data - nope. Typically in HEP, there are no uncertainties on data (observations). The uncertainties are all on the monte-carlo/expected rates. |
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Hi Giordon
actually we have the case in a) for any and all unfolded measurements : the unfolding procedure transfers experimental uncertainties onto the unfolded data. So then if you are doing a fit on unfolded data , you need this (this is exactly the use case I had in mind)
b) shame ! What if the data stat uncertainties are correlated ? For example fitting two searches which are not orthogonal but where you know the correlation
anyway, we did both those things by hand with Minuit, but would be cool if central tools supported these not so crazy use cases !
Louie