Uncertainty in Artificial Intelligence
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Causal Reasoning in Graphical Time Series Models
Michael Eichler, Vanessa Didelez
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.
Pages: 109-116
PS Link:
PDF Link: /papers/07/p109-eichler.pdf
AUTHOR = "Michael Eichler and Vanessa Didelez",
TITLE = "Causal Reasoning in Graphical Time Series Models",
BOOKTITLE = "Proceedings of the Twenty-Third Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-07)",
ADDRESS = "Corvallis, Oregon",
YEAR = "2007",
PAGES = "109--116"

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