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Joel Heinrich

Publications and source records attributed to Joel Heinrich.

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Interval estimation in the presence of nuisance parameters. 1. Bayesian approach

We address the common problem of calculating intervals in the presence of systematic uncertainties. We aim to investigate several approaches, but here describe just a Bayesian technique for setting upper limits. The particular example we study is that of inferring the rate of a Poisson process when there are uncertainties on the acceptance and the background. Limit calculating software associated with this work is available in the form of C functions.

physics.data-an

Pitfalls of Goodness-of-Fit from Likelihood

The value of the likelihood is occasionally used by high energy physicists as a statistic to measure goodness-of-fit in unbinned maximum likelihood fits. Simple examples are presented that illustrate why this (seemingly intuitive) method fails in practice to achieve the desired goal.

physics.data-an