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 www.bayesianrisk.com
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