1 / 38

New Developments in Bayesian Network Software ( AgenaRisk )

New Developments in Bayesian Network Software ( AgenaRisk ) Fifth Annual Conference of the Australasian Bayesian Network Modelling Society (ABNMS2013), Hobart, Tasmania , 28 Nov 2013. Norman Fenton Web: www.AgenaRisk.com Email: norman@agenarisk.com. Key differentiating features.

fonda
Télécharger la présentation

New Developments in Bayesian Network Software ( AgenaRisk )

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. New Developments in Bayesian Network Software (AgenaRisk) Fifth Annual Conference of the Australasian Bayesian Network Modelling Society (ABNMS2013), Hobart, Tasmania,28 Nov 2013 Norman Fenton Web: www.AgenaRisk.com Email: norman@agenarisk.com

  2. Key differentiating features Risk Table view (tailorable questionnaire) Multiple scenarios Simulation and dynamic discretization (leading to intelligent parameter and table learning) Sensitivity analysis and multivariate analysis Binary factorization Parameter Passing between models Ranked nodes Comprehensive models and tutorials A free version with full standard BN functionality

  3. Sensitivity analyser Multivariate analyser Risk explorer view (linked BNOs Simulation node tool Simulation node Ranked node

  4. Expanding a node monitor Statistics State values

  5. Changing graph defaults

  6. Defining the states of a numeric (simulation node) That’s it. No need to worry about discretization intervals

  7. Static v Dynamic Discretization

  8. Static v Dynamic Discretization Result has mean 25 Result has mean 30

  9. Multiple scenarios

  10. Multiple scenarios in Risk Table view

  11. Sensitivity Analyser

  12. Sensitivity Analyser

  13. Sensitivity Analyser Results

  14. Statistical distributions

  15. Parameter learning: priors

  16. Parameter learning: 2 data points

  17. Parameter learning: 7 data points

  18. Parameter learning: inconsistent data

  19. Binary factorization

  20. Parameter Passing

  21. Parameter Passing Solves classic BN problem of how to access just the summary statistics for a node

  22. Ranked nodes example

  23. Whole NPT defined in seconds

  24. Whole NPT defined in seconds

  25. Priors

  26. Impact of some observations

  27. Add testing effort

  28. Now backwards inference

  29. Only want to spend minimal effort

  30. ..and staff have average experience

  31. Change the scale

  32. Instant rescaling

  33. AgenaRisk Versions Also API Version available

  34. Supporting Book CRC Press, ISBN: 9781439809105 , ISBN 10: 1439809100 www.bayesianrisk.com

  35. Supporting Book Chapters 1. There is more to assessing risk than statistics 2. The need for causal explanatory models in risk assessment 3. Measuring uncertainty: the inevitability of subjectivity 4. The Basics of Probability 5. Bayes Theorem and Conditional Probability 6. From Bayes Theorem to Bayesian Networks 7. Defining the Structure of Bayesian Networks 8. Building and Eliciting Probability Tables 9. Numeric Variables and Continuous Distribution Functions 10. Hypothesis Testing and Confidence Intervals 11. Modeling Operational Risk 12. Systems Reliability Modeling 13. Bayes and the Law Plus extensive resources and models at www.bayesianrisk.com

  36. Future Releases Version 6.1 (Dec 2013) New algorithm with enhanced DD accuracy and efficiency Many additional models Web services version BAYES-KNOWLEDGE add-ons www.eecs.qmul.ac.uk/~norman/projects/B_Knowledge.html

More Related