Probabilities of Causation and Root Cause Analysis with Quasi-Markovian Models
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Abstract (arXiv)
Probabilities of causation provide principled ways to assess causal relationships but face computational challenges due to partial identifiability and latent confounding. This paper introduces both algorithmic simplifications, significantly reducing the computational complexity of calculating tighter bounds for these probabilities, and a novel methodological framework for Root Cause Analysis that systematically employs these causal metrics to rank entire causal paths.
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References · 6
- 2013Counterfactual Probabilities: Computational Methods, Bounds and Applicationscited by 67
- 2019Causal structure based root cause analysis of outlierscited by 65
- 2021Partial Counterfactual Identification from Observational and Experimental Datacited by 64
- 2022Causal Inference-Based Root Cause Analysis for Online Service Systems with Intervention Recognitioncited by 56
- 2024A Comprehensive Survey on Root Cause Analysis in (Micro) Services: Methodologies, Challenges, and Trendscited by 10
- 2023Efficient Computation of Counterfactual Boundscited by 8
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