Kernel canonical-correlation Granger causality for multiple time series

2011 ◽  
Vol 83 (4) ◽  
Author(s):  
Guorong Wu ◽  
Xujun Duan ◽  
Wei Liao ◽  
Qing Gao ◽  
Huafu Chen
Keyword(s):  
Time Series ◽  
Granger Causality ◽  
Canonical Correlation ◽  
Multiple Time ◽  
Multiple Time Series

scholarly journals Causal inference with multiple time series: principles and problems

2013 ◽  
Vol 371 (1997) ◽  
pp. 20110613 ◽  
Author(s):  
Michael Eichler
Keyword(s):  
Time Series ◽  
Causal Inference ◽  
Granger Causality ◽  
Latent Variables ◽  
Time Series Data ◽  
Series Data ◽  
Multiple Time ◽  
Identification Algorithm ◽  
Multiple Time Series ◽  
Theoretical Justification

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.

scholarly journals Inferring pairwise regulatory relationships from multiple time series datasets

2007 ◽  
Vol 23 (6) ◽  
pp. 755-763 ◽  
Author(s):  
Y. Shi ◽  
T. Mitchell ◽  
Z. Bar-Joseph
Keyword(s):  
Time Series ◽  
Multiple Time ◽  
Multiple Time Series
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