Abstract
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.
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Sameshima, K., Takahashi, D.Y., Baccalá, L.A. (2014). On the Statistical Performance of Connectivity Estimators in the Frequency Domain. In: Ślȩzak, D., Tan, AH., Peters, J.F., Schwabe, L. (eds) Brain Informatics and Health. BIH 2014. Lecture Notes in Computer Science(), vol 8609. Springer, Cham. https://doi.org/10.1007/978-3-319-09891-3_38
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DOI: https://doi.org/10.1007/978-3-319-09891-3_38
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09890-6
Online ISBN: 978-3-319-09891-3
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