Confidence in Probabilistic Risk Assessment

Epistemic uncertainties are included in probabilistic risk assessment (PRA) as second-order probabilities that represent the degrees of belief of the scientists that a model is correct. In this article, I propose an alternative approach that incorporates the scientist’s confidence in a probability set for a given quantity. First, I give some arguments against the use of precise probabilities to estimate scientific uncertainty in risk analysis. I then extend the “confidence approach” developed by Brian Hill and Richard Bradley to PRA. Finally, I claim that this approach represents model uncertainty better than the standard (Bayesian) model does

Bayesian probability · Confidence interval · Econometrics · Epistemology · Machine learning · Probabilistic logic · Probabilistic risk assessment · Set (abstract data type) · Statistics · Uncertainty quantification · Artificial Intelligence · Computer Science · Epistemology, Ethics, and Metaphysics · Mathematics · Philosophy · Philosophy and History of Science · Risk Perception and Management

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