Sensitivity analysis of probabilistic networks. (English) Zbl 1117.90068
Lucas, Peter (ed.) et al., Advances in probabilistic graphical models. Selected papers based on the presentations at the 2nd European workshop on probabilistic graphical models (PGM 2004), Leiden, The Netherlands, October 4–8, 2004. Berlin: Springer (ISBN 978-3-540-68994-2/bhk). Studies in Fuzziness and Soft Computing 213, 103-124 (2007).
Summary: Sensitivity analysis is a general technique for investigating the robustness of the output of a mathematical model and is performed for various different purposes. The practicability of conducting such an analysis of a probabilistic network has recently been studied extensively, resulting in a variety of new insights and effective methods, ranging from properties of the mathematical relation between a parameter and an output probability of interest, to methods for establishing the effects of parameter variation on decisions based on the output distribution computed from a network. In this paper, we present a survey of some of these research results and explain their significance.
For the entire collection see [Zbl 1108.90003].
For the entire collection see [Zbl 1108.90003].
MSC:
| 90C31 | Sensitivity, stability, parametric optimization |
| 90B15 | Stochastic network models in operations research |
