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

Abstract

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
Pages103-124
Number of pages22
DOIs
Publication statusPublished - 2007

Publication series

NameStudies in Fuzziness and Soft Computing
Volume213
ISSN (Print)1434-9922

Cite this