Analytical approach to network inference: Investigating degree distribution

Gloria Cecchini, Bjoern Schelter

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
10 Downloads (Pure)


When the network is reconstructed, two types of errors can occur: false positive and false negative errors about the presence or absence of links. In this paper, the influence of these two errors on the vertex degree distribution is analytically analysed. Moreover, an analytic formula of the density of the biased vertex degree distribution is found. In the inverse problem, we find a reliable procedure to reconstruct analytically the density of the vertex degree distribution of any network based on the inferred network and estimates for the false positive and false negative errors based on, e.g., simulation studies.
Original languageEnglish
Article number022311
Number of pages10
JournalPhysical Review. E, Statistical, Nonlinear and Soft Matter Physics
Issue number2
Early online date13 Aug 2018
Publication statusPublished - Aug 2018

Bibliographical note

The authors thank Dr. Daniel Vogel for helpful comments and discussions. 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.


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