Abstract
The principle of applying a Bayesian Method using Markov Chain Monte Carlo sampling for the evaluation of segmented gamma scanning data for waste packages containing gamma-emitting radioactive waste including additional a-priori information is described in general and its application is demonstrated on simulated and measured data.
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