2021
DOI: 10.3390/e23101308
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Causal Algebras on Chain Event Graphs with Informed Missingness for System Failure

Abstract: Graph-based causal inference has recently been successfully applied to explore system reliability and to predict failures in order to improve systems. One popular causal analysis following Pearl and Spirtes et al. to study causal relationships embedded in a system is to use a Bayesian network (BN). However, certain causal constructions that are particularly pertinent to the study of reliability are difficult to express fully through a BN. Our recent work demonstrated the flexibility of using a Chain Event Grap… Show more

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Cited by 7 publications
(3 citation statements)
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“…Paper [11] studies causal algebras on Chain Event Graphs (CEG). One popular causal analysis following Pearl [12] and Spirtes et al [13] to study causal relationships embedded in a system is to use a Bayesian Network (BN).…”
Section: Causal Models and Modeling Under Interventions Papermentioning
confidence: 99%
See 2 more Smart Citations
“…Paper [11] studies causal algebras on Chain Event Graphs (CEG). One popular causal analysis following Pearl [12] and Spirtes et al [13] to study causal relationships embedded in a system is to use a Bayesian Network (BN).…”
Section: Causal Models and Modeling Under Interventions Papermentioning
confidence: 99%
“…However, certain causal constructions that are particularly pertinent to the study of reliability are difficult to express fully through a BN. The previous work of the authors of [ 11 ] demonstrated that an event tree rather than a BN could provide an alternative framework that could capture most of the causal concepts needed within this domain. A causal calculus for a specific type of intervention, called a remedial intervention, was devised on this tree-like graph.…”
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confidence: 99%
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