A flexible method for parameterizing ranked nodes in Bayesian networks using Beta distributions
Author:
Affiliation:
1. Bayesian Intelligence Upwey Victoria Australia
Publisher
Wiley
Subject
Physiology (medical),Safety, Risk, Reliability and Quality
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1111/risa.13915
Reference37 articles.
1. “Conditional Inter-Causally Independent” node distributions, a property of “noisy-or” models
2. Alkhairy I. Low‐Choy S. &Hallgren W.(2017).Designing elicitation of expert knowledge into conditional probability tables in Bayesian networks: Choosing scenarios. In22nd International Congress on Modelling and Simulation(Vol. 3 pp.1069–1075). Hobart Tasmania Australia.
3. Quantifying conditional probability tables in Bayesian networks: Bayesian regression for scenario-based encoding of elicited expert assessments on feral pig habitat
4. Balancing the Elicitation Burden and the Richness of Expert Input When Quantifying Discrete Bayesian Networks
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1. Bayesian networks for risk analysis and decision support;Risk Analysis;2022-06
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