arXiv stat.ML
· Papers
Re-examining Granger Causality with Causal Bayesian Networks and Reichenbachs Principles
arXiv:2501.02672v4 Announce Type: replace Abstract: Granger causality (GC) is widely used to infer directed relationships in time-series data. However, its predictive criterion does not by itself distinguish direct causal effects from dependencies induced by common causes, indirect paths, collider conditioning, or mode