Bayesian approach for quantifying the uncertainty of neutron doses derived from spectrometric measurements.
Bayesian methods provide a unified framework for combining information in the presence of uncertainty. All uncertainties that enter into the description of a measurement are modelled using probability distributions, and these are handled according to the rules of probability theory, ensuring that the approach is free of inconsistencies. The final result of the analysis is the full probability distribution for the parameter of interest, and from this distribution an appropriate uncertainty interval can be obtained. Some of the advantages of a Bayesian analysis include a straightforward approach to the problem of dealing with nuisance parameters, the ability to incorporate prior information in a natural way and the flexibility that is necessary for a realistic modelling of the measurement process. As an example, the problem of deriving neutron dose estimates and their uncertainties based on measurements carried out using a Bonner sphere spectrometer is considered.
Reginatto
M
M
Physikalisch-Technische Bundesanstalt, D-38116 Braunschweig, Germany. Marcel.Reginatto@ptb.de
D001499:Bayes Theorem; D003627:Data Interpretation, Statistical; D015233:Models, Statistical; D009010:Monte Carlo Method; D009502:Neutrons; D011336:Probability; D011874:Radiometry / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software; D013053:Spectrophotometry / Q000379:methods*; D035501:Uncertainty