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| Titel |
Estimating time delays for constructing dynamical networks |
| VerfasserIn |
E. A. Martin, J. Davidsen |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 21, no. 5 ; Nr. 21, no. 5 (2014-09-11), S.929-937 |
| Datensatznummer |
250120939
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| Publikation (Nr.) |
 copernicus.org/npg-21-929-2014.pdf |
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| Zusammenfassung |
| Dynamical networks – networks inferred from multivariate time series – have
been widely applied to climate data and beyond, resulting in new insights
into the underlying dynamics. However, these inferred networks can suffer
from biases that need to be accounted for to properly interpret the results.
Here, we report on a previously unrecognized bias in the estimate of time
delays between nodes in dynamical networks inferred from cross-correlations,
a method often used. This bias results in the maximum correlation occurring
disproportionately often at large time lags. This is of particular concern in
dynamical networks where the large number of possible links necessitates
finding the correct time lag in an automated way. We show that this bias can
arise due to the similarity of the estimator to a random walk, and are able
to map them to each other explicitly for some cases. For the random walk
there is an analytical solution for the bias that is closely related to the
famous Lévy arcsine distribution, which provides an upper bound in many
other cases. Finally, we show that estimating the cross-correlation in
frequency space effectively eliminates this bias. Reanalysing large lag links
(from a climate network) with this method results in a distribution peaked
near zero instead, as well as additional peaks at the originally assigned
lag. Links that are reassigned smaller time lags tend to have a smaller
distance between them, which indicates that the new time delays are
physically reasonable. |
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