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dc.contributor.authorDiego, David
dc.contributor.authorHaaga, Kristian Agasøster
dc.contributor.authorHannisdal, Bjarte
dc.date.accessioned2020-04-16T07:20:33Z
dc.date.available2020-04-16T07:20:33Z
dc.date.issued2019
dc.PublishedDiego D, Haaga KA, Hannisdal B. Transfer entropy computation using the Perron-Frobenius operator. Physical review. E. 2019;99(4): 042212eng
dc.identifier.issn2470-0045en_US
dc.identifier.issn2470-0053en_US
dc.identifier.urihttps://hdl.handle.net/1956/21882
dc.description.abstractWe propose a method for computing the transfer entropy between time series using Ulam's approximation of the Perron-Frobenius (transfer) operator associated with the map generating the dynamics. Our method differs from standard transfer entropy estimators in that the invariant measure is estimated not directly from the data points, but from the invariant distribution of the transfer operator approximated from the data points. For sparse time series and low embedding dimension, the transfer operator is approximated using a triangulation of the attractor, whereas for data-rich time series or higher embedding dimension, we use a faster grid approach. We compare the performance of our methods with existing estimators such as the k nearest neighbors method and kernel density estimation method, using coupled instances of well known chaotic systems: coupled logistic maps and a coupled Rössler-Lorenz system. We find that our estimators are robust against moderate levels of noise. For sparse time series with less than 100 observations and low embedding dimension, our triangulation estimator shows improved ability to detect coupling directionality, relative to standard transfer entropy estimators.en_US
dc.language.isoengeng
dc.publisherAPSen_US
dc.titleTransfer entropy computation using the Perron-Frobenius operatoren_US
dc.typePeer reviewed
dc.typeJournal article
dc.date.updated2020-02-18T14:33:41Z
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2019 American Physical Societyen_US
dc.identifier.doihttps://doi.org/10.1103/physreve.99.042212
dc.identifier.cristin1713342
dc.source.journalPhysical review. E


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