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Confidence, Statistical Evidence and Relative Belief with...
[Submitted on 8 Jun 2026] · 2026-06-10 · via stat updates on arXiv.org

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Abstract:Probability theory provides a clear definition of what is meant by evidence in favor, against or none either way, of an event occurring for an unobserved response, via the principle of evidence. This is immediately applicable when carrying out a proper Bayesian analysis. Even without a prior, this imposes restrictions on reported inferences as these need to reflect the likelihood ordering. Relative belief inferences satisfy this requirement and, when the errors in these inferences are controlled, they also satisfy repeated sampling, or frequentist, requirements such as achieving given confidence levels. Relative belief inferences are considered here for the construction of intervals for uncertainty quantification in the context of a Poisson model for a signal with background noise. These intervals are contrasted with the well-known Feldman-Cousins intervals for this problem.

Submission history

From: Michael Evans [view email]
[v1] Mon, 8 Jun 2026 23:48:47 UTC (343 KB)