This paper studies the performance of recently introduced asymptotic statistics for connectivity inference in the frequency domain, namely via information partial directed coherence (iPDC) and information directed transfer function (iDTF) and compares them to the behaviour of a classic time domain multivariate Granger causality test (GCT) by using Monte Carlo simulations of three widely used toy-models under varying the simulated data record lengths. In general, the false-positive rates for non-existing connections and the false-negative rates for existing connections are found to decrease with longer record lengths. © 2014 Springer International Publishing.
CITATION STYLE
Sameshima, K., Takahashi, D. Y., & Baccalá, L. A. (2014). On the statistical performance of connectivity estimators in the frequency domain. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8609 LNAI, pp. 412–423). Springer Verlag. https://doi.org/10.1007/978-3-319-09891-3_38
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