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Causal algebras on chain event graphs with informed missingness for system failure
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Yu, Xuewen and Smith, Jim Q (2021) Causal algebras on chain event graphs with informed missingness for system failure. Entropy, 23 (10). e1308. doi:10.3390/e23101308 ISSN 1099-4300.
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Official URL: https://doi.org/10.3390/e23101308
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 Graph (CEG) instead to capture causal reasoning embedded within engineers’ reports. We 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. In particular, a causal calculus for a specific type of intervention, called a remedial intervention, was devised on this tree-like graph. In this paper, we extend the use of this framework to show that not only remedial maintenance interventions but also interventions associated with routine maintenance can be well-defined using this alternative class of graphical model. We also show that the complexity in making inference about the potential relationships between causes and failures in a missing data situation in the domain of system reliability can be elegantly addressed using this new methodology. Causal modelling using a CEG is illustrated through examples drawn from the study of reliability of an energy distribution network.
Item Type: | Journal Article | |||||||||||||||
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Subjects: | Q Science > QA Mathematics | |||||||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | |||||||||||||||
SWORD Depositor: | Library Publications Router | |||||||||||||||
Library of Congress Subject Headings (LCSH): | Bayesian statistical decision theory, Mathematical statistics -- Graphic methods, Trees (Graph theory) | |||||||||||||||
Journal or Publication Title: | Entropy | |||||||||||||||
Publisher: | M D P I AG | |||||||||||||||
ISSN: | 1099-4300 | |||||||||||||||
Official Date: | 6 October 2021 | |||||||||||||||
Dates: |
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Volume: | 23 | |||||||||||||||
Number: | 10 | |||||||||||||||
Article Number: | e1308 | |||||||||||||||
DOI: | 10.3390/e23101308 | |||||||||||||||
Status: | Peer Reviewed | |||||||||||||||
Publication Status: | Published | |||||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | |||||||||||||||
Date of first compliant deposit: | 27 October 2021 | |||||||||||||||
Date of first compliant Open Access: | 27 October 2021 | |||||||||||||||
RIOXX Funder/Project Grant: |
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