Confronting classical and Bayesian confidence limits to examples

Classical confidence limits are compared to Bayesian error bounds by studying relevant examples. The performance of the two methods is investigated relative to the properties coherence, precision, bias, universality, simplicity. A proposal to define error limits in various cases is derived from the comparison. It is based on the likelihood function only and follows in most cases the general practice in high energy physics. Classical methods are discarded because they violate the likelihood principle, they can produce physically inconsistent results, suffer from a lack of precision and generality. Also the extreme Bayesian approach with arbitrary choice of the prior probability density or priors deduced from scaling laws is rejected.Comment: 16 pages, 12 figure

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Including gaussian uncertainty on the background estimate for upper limit calculations using Poissonian sampling

A procedure to include the uncertainty on the background estimate for upper limit calculations using Poissonian sampling is presented for the case where a Gaussian assumption on the uncertainty can be made. Under that hypothesis an analytic expression of the likelihood is derived which can be written in terms of polynomials defined by recursion. This expression may lead to a significant speed up of computing applications that extract the upper limits using Toy Monte Carlo.Comment: 6 pages, 2 figures, accepted for publication in Nucl.Instrum.Meth.