期刊
出版社
ROYAL SOC
DOI: 10.1098/rsta.2011.0613
关键词
causal identification; Granger causality; causal effect; spurious causality; latent variables; impulse response function
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 nontechnical and thus accessible to applied scientists who are interested in adopting the method.
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