Aspects of the integration of different data sources are discussed with respect to improvement of reliability and significance of experimental results. Thomson scattering data have been analysed by means of Bayesian probability theory. This much improved s
Fig. 2: Bayesian graph for joint evaluation of electron temperature and density profiles, including a mapping on magnetic surfaces. The bottom sections represent subgraphs for different diagnostics.
Integration of further diagnostics is done by adding further subgraphs representing those
information sources.
Conclusion
BPT provides outstanding tools for statistical modelling allowing the combination of
uncertainties from different sources. Deep cooperation with diagnosticians result in error
analyses which allow for a quantitative comparison of data from different diagnostics. The feasibility of this approach was shown for a Thomson scattering diagnostics. On the basis
of this thorough error analysis, the uncertainties due to combination of different diagnostics sources becomes quantifiable. Again, the Bayesian framework allows for a rigorous
combination of different data. Realisation of that approach is the next step towards an
integrated data analysis.
References
[1] G. Cordey, D. McDonald, et al., private communications
[2] J.J. Jeffreys, Theory of Probability, Oxford University Press, 1939.
[3] D.S. Sivia, Data Analysis – A Bayesian Tutorial, Clarendon Press, 1996.
[4] R. Fischer, C. Wendland, A. Dinklage, et al., Plasma Phys. Contr. Fusion (accepted).
[5] K. Mc Cormick, et al., Phys. Rev. Lett. (2002) (at press).
[6] H. Bindslev, Rev. Sci. Instrum. 70, 1093 (1999).
[7] Steffen L. Lauritzen, Graphical Models, Oxford University Press, 1996.
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