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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:

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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

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

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Expanding a node monitor Statistics State values

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Changing graph defaults

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Defining the states of a numeric (simulation node) Thats it. No need to worry about discretization intervals

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Static v Dynamic Discretization

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Result has mean 25 Result has mean 30

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Multiple scenarios

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Multiple scenarios in Risk Table view

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Sensitivity Analyser

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Sensitivity Analyser Results

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Statistical distributions

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Parameter learning: priors

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Parameter learning: 2 data points

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Parameter learning: 7 data points

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Parameter learning: inconsistent data

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Binary factorization

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Parameter Passing

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

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Ranked nodes example

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Whole NPT defined in seconds

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Priors

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Impact of some observations

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Add testing effort

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Now backwards inference

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Only want to spend minimal effort

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..and staff have average experience

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Change the scale

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Instant rescaling

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AgenaRisk Versions AgenaRisk Free AgenaRisk Lite AgenaRisk Pro Open and run any modelYes Risk map, risk table, and risk explorer viewsYes Fully configurable risk graphsYes Sensitivity analysisYes Multivariate analysisYes Import/export functionalityYes Create new modelYes Pre-supplied models, tutorials, User manualYes Save Model containing just Boolean and labelled nodes Yes Save model containing ranked nodesmax 5max 10Unlimited Save model containing simulation nodesmax 5max 10Unlimited Save model containing multiple BNOsmax 2max 5Unlimited Maintenance supportNone Unlimited UpgradesNone Unlimited CostFreeFree to buyers of book Subscription Also API Version available

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Supporting Book CRC Press, ISBN: , ISBN 10:

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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 Supporting Book Chapters Plus extensive resources and models at

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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

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