Characterization and evaluation of uncertainty in probabilistic risk analysis

Abstract

The sources of uncertainty in probabilistic risk analysis are discussed, using the event and fault-tree methodology as an example. The role of statistics in quantifying these uncertainties is investigated. A class of uncertainties is identified which are, at present, unquantifiable using either classical or Bayesian statistics. it is argued that Bayesian statistics is the more appropriate vehicle for the probabilistic analysis of rare events, and a short review is given with some discussion on the representation of ignorance.