Cecchini Gloria, Cestnik Rok, Pikovsky Arkady
CSDC, Department of Physics and Astronomy, University of Florence, Sesto Fiorentino, Florence, Italy.
Institute of Physics and Astronomy, University of Potsdam, Campus Golm, Karl-Liebknecht-Straße 24/25, 14476 Potsdam-Golm, Germany.
Phys Rev E. 2021 Feb;103(2-1):022305. doi: 10.1103/PhysRevE.103.022305.
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.
当从数据中推断网络时,可能会出现两种类型的错误:关于链接存在的假阳性和假阴性结论。在耦合振子网络的情况下,我们关注局部网络特征对假阳性结论概率α和假阴性结论概率β的影响。我们证明,假结论概率受局部连通性度量(如最短路径长度和迂回度)的影响,当真实的基础网络事先未知时,这些度量也可以从推断出的网络中估计出来。然后,这些度量可用于量化链接结论的置信水平,并通过链接权重阈值化的先进概念来改进网络重建。