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| Titel |
Consistently weighted measures for complex network topologies |
| VerfasserIn |
Jobst Heitzig, Norbert Marwan, Yong Zou, Jonathan F. Donges, Jürgen Kurths |
| Konferenz |
EGU General Assembly 2010
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 12 (2010) |
| Datensatznummer |
250033064
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| Zusammenfassung |
| Most measures of the structural and topological properties of a complex network are of a
combinatorial nature, basically counting certain nodes, edges, triangles, paths, etc. But the
typically finite set of nodes of the studied network is often either explicitly or implicitly
considered representative of a much larger finite or infinite set of objects of interest, either by
being a subset of this larger set or by being some kind of discretisation or aggregation of it.
Examples are networks consisting of a statistically sampled number of members of a large
social or scientific community, networks of discrete regular grid points on a surface or of
irregular mesh cells in some manifold, or networks constructed from recurrence plots of time
series with regular or irregular time intervals. This selection procedure typically
results in individual nodes of the studied network representing quite differently sized
regions of the domain of interest, inducing substantial biases in derived network
statistics.
To avoid these problems, we propose an axiomatic scheme based on the idea of node
splitting invariance to derive consistently weighted variants of various commonly used
statistical network measures which approximate the corresponding properties of the
underlying domain of interest. The practical relevance and applicability of our approach is
demonstrated for the example of climate networks — networks constructed from climate data
on grids with heterogenous mesh cell areas. |
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