Evidence-invariant Sensitivity Bounds

Silja Renooij; Linda C. van der Gaag

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arXiv · 1207.4170

Evidence-invariant Sensitivity Bounds

Silja Renooij·Linda C. van der Gaag

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Abstract

The sensitivities revealed by a sensitivity analysis of a probabilistic network typically depend on the entered evidence. For a real-life network therefore, the analysis is performed a number of times, with different evidence. Although efficient algorithms for sensitivity analysis exist, a complete analysis is often infeasible because of the large range of possible combinations of observations. In this paper we present a method for studying sensitivities that are invariant to the evidence entered. Our method builds upon the idea of establishing bounds between which a parameter can be varied without ever inducing a change in the most likely value of a variable of interest.

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Silja Renooij, Linda C. van der Gaag. 2012-07-11. Evidence-invariant Sensitivity Bounds. https://arxiv.org/abs/1207.4170

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