Asymptotic formulae for likelihood-based tests of new physics
Асимптотические формулы для вероятностно-ориентированных тестов новой физики
2011-02-01
SCID: 54.1/78dey9s8
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Asimov data setWald approximationWilks' theoremasymptotic distributionslikelihood-based statistical tests
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Abstract (AI)
We describe likelihood-based statistical tests for use in high energy physics for the discovery of new phenomena and for construction of confidence intervals on model parameters. We focus on the properties of the test procedures that allow one to account for systematic uncertainties. Explicit formulae for the asymptotic distributions of test statistics are derived using results of Wilks and Wald. We motivate and justify the use of a representative data set, called the “Asimov data set”, which provides a simple method to obtain the median experimental sensitivity of a search or measurement as well as fluctuations about this expectation.
Key Findings
1
Explicit asymptotic formulae for distributions of test statistics are derived using Wilks' and Wald's results.
2
Introduction and justification of the 'Asimov data set' as a representative dataset to obtain median experimental sensitivity and expected fluctuations.
3
Likelihood-based statistical tests are described for discovery and confidence-interval construction in high energy physics, including treatment of systematic uncertainties.
4
The Asimov data set provides a simple method to compute median sensitivity and its variations without extensive Monte Carlo simulation.
Research Object
Likelihood-based statistical tests for discovery of new phenomena and confidence-interval construction in high-energy physics
Research Subject
Asymptotic distributions and properties of test statistics (including treatment of systematic uncertainties) and use of the Asimov dataset to obtain median experimental sensitivity and expected fluctuations
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2011-02-01
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