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Bayesian inferences in high energy physics often use uniform prior distributions for parameters about which little or no information is available before data are collected.
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There is no agreement on what to call such priors. In the literature one finds many names: objective, non-subjective, non-informative, minimally-informative, default, neutral, conventional, reference. However, we prefer the term formal prior because it reflects the manner in which they are constructed
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In our calculations we have used the approximation d 2 f / d σ 2 ≈ [ 4 D ( f , h ) / 3 − D ( f , 2 h ) / 12 ] / h 2 + ○ ( h 4 ) d^{2}f/d\sigma^{2}\approx[4D(f,h)/3-D(f,2h)/12]/h^{2}+\bigcirc(h^{4}) , where D ( f , h ) = f ( σ + h ) − 2 f ( σ ) + f ( σ − h ) D(f,h)=f(\sigma+h)-2f(\sigma)+f(\sigma-h) and h h is the step size
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