Abstract
When a network is inferred from data, two types of errors can occur: false positive and false negative conclusions about the presence of links. We focus on the influence of local network characteristics on the probability α of false positive conclusions, and on the probability β of false negative conclusions, in the case of networks of coupled oscillators. We demonstrate that false conclusion probabilities are influenced by local connectivity measures such as the shortest path length and the detour degree, which can also be estimated from the inferred network when the true underlying network is not known a priori. These measures can then be used for quantification of the confidence level of link conclusions, and for improving the network reconstruction via advanced concepts of link weights thresholding.
Original language | English |
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Article number | 022305 |
Pages (from-to) | 1-8 |
Number of pages | 8 |
Journal | Physical review E |
Volume | 103 |
Issue number | 2 |
Early online date | 8 Feb 2021 |
DOIs | |
Publication status | Published - Feb 2021 |
Bibliographical note
Funding Information:This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 642563. A.P. thanks Russian Science Foundation (Grant No. 17-12-01534). The authors declare no competing financial interests.
Publisher Copyright:
© 2021 American Physical Society.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
Funding
This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 642563. A.P. thanks Russian Science Foundation (Grant No. 17-12-01534). The authors declare no competing financial interests.
Funders | Funder number |
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Horizon 2020 Framework Programme | |
Russian Science Foundation | 17-12-01534 |
Horizon 2020 | 642563 |