Open Access
EPJ Web of Conferences
Volume 55, 2013
SOS 2012 – IN2P3 School of Statistics
Article Number 03003
Number of page(s) 29
Section Application to Data Analyses
Published online 01 July 2013
  1. J. Neyman, E. Pearson, “On the Problem of the Most Efficient Tests of Statistical Hypotheses”, Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character, 231 (1933) 289. [NASA ADS] [CrossRef]
  2. S. Wilks, “The large-sample distribution of the likelihood ratio for testing composite hypotheses”, Ann. Math. Stat., 9 (1938) 60. [CrossRef]
  3. S. Baker, R.D. Cousins, “Clarification of the use of chi-square and likelihood functions in fit to histograms”, Nucl. Instr. Meth., A221 (1984), 437.
  4. G. Cowan, K. Cranmer, E. Gross and O. Vitells, “Asymptotic formulae for likelihood-based tests of new physics”, Eur.Phys.J. C71 (2011) 1554.
  5. O. Helene, “Upper limit of peak area”, Nucl. Instr. and Meth. A212 (1983) 319.
  6. G. D’Agostini, “Bayesian Reasoning in Data Analysis: A Critical Introduction”, World Scientific (2003) ISBN 981-238-356-5,
  7. J. Jeffreys, “An Invariant Form for the Prior Probability in Estimation Problems”, Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences 186 no. 1007 ((1946) 453. [NASA ADS] [CrossRef] [PubMed]
  8. G. Zech, “Upper limits in experiments with background or measurement errors”, Nucl. Instr. and Meth. A277 (1989) 608.
  9. V.L. Highland, R.D. Cousins, “Comment on “Upper limits in experiments with background or measurement errors” [Nucl. Instr. and Meth. A 277 (1989) 608–610]”,
  10. Nucl. Instr. and Meth. A398 (1989), 429.
  11. G. Zech, “Reply to “Comment on “Upper limits in experiments with background or measurement errors” [Nucl. Instr. and Meth. A 277 (1989) 608-610]” ”, [NASA ADS] [CrossRef]
  12. Nucl. Instr. and Meth. A398 (1989) 431.
  13. J.Neyman, J, “Outline of a theory of statistical estimation based on the clasiscal theory of probability”, Philosophical Transactions of the Royal Society of London, A236, no. 767 (1937), 333.
  14. G.J. Feldman, R.D. Cousins, “Unified approach to the classical statistical analysis of small signals”, Phys. Rev. D57 (1998) 3873.
  15. C. Amsler, C. it et al. (Particle Data Group), “The Review of Particle Physics”, Phys. Lett. B667 (2008) 1.
  16. G. Abbiendi et al. (The LEP Working Group for Higgs Boson Searches), “Search for the Standard Model Higgs Boson at LEP”, Phys. Lett. B565 (2003) 61.
  17. A.L. Read, “Modified frequentist analysis of search results (the CLs method)”, 1st Workshop on Confidence Limits", CERN (2000).
  18. B.A. Berg, “Markov Chain Monte Carlo Simulations and Their Statistical Analysis”, World Scientific", Singapore (2004).
  19. R.D. Cousins, V.L. Highland, “Incorporating Syst ematic Uncertainties into an Upper Limit”, Nucl. Instr. Meth. A320 (1992) 331.
  20. L. Lista, “Including gaussian uncertainty on the background estimate for upper limit calculations using Poissonian sampling”, Nucl. Instr. Meth. A517 (2004) 360.
  21. G. Cowan et al., “Asymptotic formulae for likelihood-based tests of new physics” EPJC 71 (2011) 1554. [CrossRef] [EDP Sciences]
  22. The ATLAS Collaboration, the CMS collaboration, the LHC Higgs combination group, “Procedure for the LHC Higgs boson search combination in Summer 2011”, ATL-PHYS-PUB-2011-IN2P3 School Of Statistics, Autrans 011, CMS NOTE-2011-005 (2011)
  23. I. Asimov, “Franchise”, in I. Asimov, “The Complete Stories”, vol. 1, Broadway Books, New York, 1990.
  24. E. Gross, O. Vitells, “Trial factors for the look elsewhere effect in high energy physics”, Eur. Phys. J. C70 (2010) 525. [NASA ADS] [CrossRef] [EDP Sciences]
  25. R.B. Davies, “Hypothesistestingwhenanuisance parameter is present only under the alternative”, Biometrika 74 (1987), 33.

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