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New Developments in Bayesian Network Software (AgenaRisk)

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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:

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 Multivariate analyser
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


15 Statistical distributions


17 Parameter learning: priors

18 Parameter learning: 2 data points

19 Parameter learning: 7 data points

20 Parameter learning: inconsistent data

21 Binary factorization

22 Parameter Passing

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

24 Ranked nodes example

25 Whole NPT defined in seconds

26 Whole NPT defined in seconds

27 Priors

28 Impact of some observations

29 Add testing effort

30 Now backwards inference

31 Only want to spend minimal effort

32 ..and staff have average experience

33 Change the scale

34 Instant rescaling

35 AgenaRisk Versions Also API Version available AgenaRisk Free
AgenaRisk Lite AgenaRisk Pro Open and run any model Yes Risk map, risk table, and risk explorer views Fully configurable risk graphs Sensitivity analysis Multivariate analysis Import/export functionality Create new model Pre-supplied models, tutorials, User manual Save Model containing just Boolean and labelled nodes Save model containing ranked nodes max 5 max 10 Unlimited Save model containing simulation nodes Save model containing multiple BNOs max 2 Maintenance support None Upgrades Cost Free Free to buyers of book Subscription Also API Version available

36 Supporting Book
CRC Press, ISBN: , ISBN 10:

37 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

38 Future Releases Version 6.1 (Dec 2013) Web services version
New algorithm with enhanced DD accuracy and efficiency Many additional models Web services version BAYES-KNOWLEDGE add-ons

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