Evidence-invariant Sensitivity Bounds

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...

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Bibliographic Details
Published in:arXiv.org 2012-07
Main Authors: Renooij, Silja, Linda C van der Gaag
Format: Article
Language:English
Subjects:
Algorithms
Invariants
Sensitivity analysis
Online Access:Get full text
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Summary: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.
ISSN:2331-8422