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Likelihood description for comparing data with simulation of limited statistics

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arxiv 1304.0735 v3 pith:AJX2I22Y submitted 2013-04-02 astro-ph.IM

classification astro-ph.IM
keywords datadescriptionparameterssimulationalternativesanalyticappearsbetter
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It is often not possible to construct a probability density function that describes the data. This can happen if there is no analytic description, and the number of parameters is too large so that it is impossible to simulate and tabulate all combinations. In these situations it is still interesting to rank simulation sets performed with different parameters in how well they compare to data. We propose a solution that appears to be better suited to this task than some of the obvious alternatives.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Applications of maximum likelihood estimations for analyzing photon counts in few atom experiments

    physics.atom-ph 2024-12 conditional novelty 5.0 of 10

    Maximum likelihood estimation on model fluorescence distributions that include light-assisted-collision loss recovers atom-number proportions in a tight optical tweezer with few-percent accuracy from about 600 test runs.

  2. State of the Ice Model in the IceCube Observatory

    astro-ph.HE 2025-07 conditional novelty 3.0 of 10

    The IceCube ice model has improved steadily since AMANDA but still does not reach the statistical floor set by its own simulation of calibration data.

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