Causal Reasoning in Graphical Time Series Models
University of Maastricht（马斯特里赫特大学）；University College London（伦敦大学学院）
英文摘要：
We propose a definition of causality for time series in terms of the effect of an intervention in one component of a multivariate time series on another component at some later point in time. Conditions for identifiability, comparable to the back-door and front-door criteria, are presented and can also be verified graphically. Computation of the causal effect is derived and illustrated for the linear case.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
