Consistent Procedure for Nuclear Data Evaluation Based on Modeling

A complete and consistent procedure to generate evaluated nuclear data files and the associated covariance matrices is presented. The novel procedure is fully based on Bayesian statistics and makes use of the theoretically formulated prior for parameter uncertainties presented by Leeb and Pigni recently. In addition the prior includes also model defects based on a statistical study of the gross structure of experimental data. Furthermore, a so-called correlated Bayesian update approach (CBUA) is proposed in order to account for a realistic treatment of systematic errors in experiments.