Uncertainty characterization of data for probabilistic risk assessment

The maximum entropy approach to uncertainty characterization is of current interest in probalistic risk assessment. For the loguniform or lognormal distributions, the quantitative definition of the distribution is obtained from the maximum entropy principle and knowledge of one parameter (e.g. mean value) of the distribution. The technique is illustrated by comparison with existing data bases. (author)