432 Pages
by
Chapman & Hall
432 Pages
by
Routledge
Also available as eBook on:
This innovative volume explores graphical models using belief functions as a representation of uncertainty, offering an alternative approach to problems where probability proves inadequate. Graphical Belief Modeling makes it easy to compare the two approaches while evaluating their relative strengths and limitations. The author examines both theory and computation, incorporating practical notes... Read more
Introduction to Graphical Belief Models. Overview of Graphical Belief Models. Probability. Basic Belief Functions. Graphical Models. Manipulating Graphical Belief Models. Specifying and Storing Valuations. Belief Functions and Probabilities. The Fusion and Propagation Algorithm. Model Exploration. Belief Risk Assessment: An Example. Fault Trees. Belief Function Models for Components. Models for Simple Series and Parallel Systems. Information (Common Parameter) Dependence. Three Examples. Belief Risk Assessment and Public Policy. Appendices: Resources for Graphical Modelers. Annotated Examples. BELIEF Package and Other Software.
Biography
Almond, Russel .G
