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August 2008 The Banff Challenge: Statistical Detection of a Noisy Signal
A. C. Davison, N. Sartori
Statist. Sci. 23(3): 354-364 (August 2008). DOI: 10.1214/08-STS260

Abstract

Particle physics experiments such as those run in the Large Hadron Collider result in huge quantities of data, which are boiled down to a few numbers from which it is hoped that a signal will be detected. We discuss a simple probability model for this and derive frequentist and noninformative Bayesian procedures for inference about the signal. Both are highly accurate in realistic cases, with the frequentist procedure having the edge for interval estimation, and the Bayesian procedure yielding slightly better point estimates. We also argue that the significance, or p-value, function based on the modified likelihood root provides a comprehensive presentation of the information in the data and should be used for inference.

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A. C. Davison. N. Sartori. "The Banff Challenge: Statistical Detection of a Noisy Signal." Statist. Sci. 23 (3) 354 - 364, August 2008. https://doi.org/10.1214/08-STS260

Information

Published: August 2008
First available in Project Euclid: 28 January 2009

zbMATH: 1329.94022
MathSciNet: MR2483908
Digital Object Identifier: 10.1214/08-STS260

Rights: Copyright © 2008 Institute of Mathematical Statistics

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Vol.23 • No. 3 • August 2008
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