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arXiv · 1301.3868

Making Sensitivity Analysis Computationally Efficient

Uffe Kjærulff·Linda C. van der Gaag
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Abstract

To investigate the robustness of the output probabilities of a Bayesian network, a sensitivity analysis can be performed. A one-way sensitivity analysis establishes, for each of the probability parameters of a network, a function expressing a posterior marginal probability of interest in terms of the parameter. Current methods for computing the coefficients in such a function rely on a large number of network evaluations. In this paper, we present a method that requires just a single outward propagation in a junction tree for establishing the coefficients in the functions for all possible parameters; in addition, an inward propagation is required for processing evidence. Conversely, the method requires a single outward propagation for computing the coefficients in the functions expressing all possible posterior marginals in terms of a single parameter. We extend these results to an n-way sensitivity analysis in which sets of parameters are studied.

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Uffe Kjærulff, Linda C. van der Gaag. 2013-01-16. Making Sensitivity Analysis Computationally Efficient. https://arxiv.org/abs/1301.3868

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