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Inference of time-dependent causal influences in Networks
2012
Biomedical Engineering
We address the challenge of detecting time-variant interactions in multivariate systems. Inferring Granger-causal interactions between processes promises to gain deeper insights into mechanisms underlying network phenomena, e.g., in the neurosciences. Renormalized partial directed coherence (rPDC) has been introduced as a means to investigate Granger causality in such multivariate systems. When using rPDC a major challenge is the reliable estimation of parameters in vector autoregressive
doi:10.1515/bmt-2012-4263
fatcat:usl447vourc6poac2l24v26x2a