Sensitivity analysis of probabilistic networks

Linda C. van der Gaag*, Silja Renooij, Veerle M.H. Coupé

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review


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.

Original languageEnglish
Title of host publicationAdvances in Probabilistic Graphical Models
EditorsPeter Lucas, Jose Gamez, Antionio Salmero
Number of pages22
Publication statusPublished - 2007

Publication series

NameStudies in Fuzziness and Soft Computing
ISSN (Print)1434-9922

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