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- aggregation classification "C3".
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation date "2007".
- aggregation format "application/pdf".
- aggregation hasFormat 1974570.bibtex.
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- aggregation hasFormat 1974570.doc.
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- aggregation language "eng".
- aggregation rights "I have retained and own the full copyright for this publication".
- aggregation subject "Mathematics and Statistics".
- aggregation title "Propagating imprecise probabilities through event trees".
- aggregation abstract "Event trees are a graphical model of a set of possible situations and the possible paths going through them, from the initial situation to the terminal situations. With each situation, there is associated a local uncertainty model that represents beliefs about the next situation. The uncertainty models can be classical, precise probabilities; they can also be of a more general, imprecise probabilistic type, in which case they can be seen as sets of classical probabilities (yielding probability intervals). To work with such event trees, we must combine these local uncertainty models. We show this can be done efficiently by back-propagation through the tree, both for precise and imprecise probabilistic models, and we illustrate this using an imprecise probabilistic counterpart of the classical Markov chain. This allows us to perform a robustness analysis for Markov chains very efficiently.".
- aggregation authorList BK324305.
- aggregation aggregates 1974571.
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