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Auteurs principaux: Østergaard, Jan, Boubakani, Payam
Format: Preprint
Publié: 2022
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Accès en ligne:https://arxiv.org/abs/2212.05728
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author Østergaard, Jan
Boubakani, Payam
author_facet Østergaard, Jan
Boubakani, Payam
contents We present a new decomposition of transfer entropy to characterize the degree of synergy- and redundancy-dominated influence a time series has upon the interaction between other time series. We prove the existence of a class of time series, where the early past of the conditioning time series yields a synergistic effect upon the interaction, whereas the late past has a redundancy-dominated effect. In general, different parts of the past can have different effects. Our information theoretic quantities are easy to compute in practice, and we demonstrate their usage on real-world brain data.
format Preprint
id arxiv_https___arxiv_org_abs_2212_05728
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Synergy and Redundancy Dominated Effects in Time Series via Transfer Entropy Decompositions
Østergaard, Jan
Boubakani, Payam
Information Theory
We present a new decomposition of transfer entropy to characterize the degree of synergy- and redundancy-dominated influence a time series has upon the interaction between other time series. We prove the existence of a class of time series, where the early past of the conditioning time series yields a synergistic effect upon the interaction, whereas the late past has a redundancy-dominated effect. In general, different parts of the past can have different effects. Our information theoretic quantities are easy to compute in practice, and we demonstrate their usage on real-world brain data.
title Synergy and Redundancy Dominated Effects in Time Series via Transfer Entropy Decompositions
topic Information Theory
url https://arxiv.org/abs/2212.05728