I carried out two sensitivity scans for a central/asimov expectation (no fluctuations in bins from their nominal values), only changing the metric, and get wildly different results. A standard Poisson LLH gives something similar to what we expect, and have seen in previous implementations (GolemFit). However, using the effective likelihood (mceff_llh) produces contours that not only mimic signal, but also exclude the nominal/central expectation at >90% CL.
I've been poking around in the code, but can't seem to find the cause of this.
I carried out two sensitivity scans for a central/asimov expectation (no fluctuations in bins from their nominal values), only changing the metric, and get wildly different results. A standard Poisson LLH gives something similar to what we expect, and have seen in previous implementations (GolemFit). However, using the effective likelihood (
mceff_llh
) produces contours that not only mimic signal, but also exclude the nominal/central expectation at >90% CL.I've been poking around in the code, but can't seem to find the cause of this.