Causal inference with multiple time series: principles and problems
2013 ◽
Vol 371
(1997)
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pp. 20110613
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I review the use of the concept of Granger causality for causal inference from time-series data. First, I give a theoretical justification by relating the concept to other theoretical causality measures. Second, I outline possible problems with spurious causality and approaches to tackle these problems. Finally, I sketch an identification algorithm that learns causal time-series structures in the presence of latent variables. The description of the algorithm is non-technical and thus accessible to applied scientists who are interested in adopting the method.
2005 ◽
Vol 33
(2)
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pp. 159-172
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2014 ◽
Vol 37
◽
pp. 301-308
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Keyword(s):
1989 ◽
Vol 10
(3)
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pp. 471-494
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Keyword(s):
Keyword(s):