Table 5 Re-creation of process generated networks.

From: Priority Attachment: a Comprehensive Mechanism for Generating Networks

Network p D p B p C |V| |E| d ρ L \({{\boldsymbol{\rho }}}_{{{\boldsymbol{C}}}_{{\boldsymbol{D}}}}^{{\bf{2}}}\) Network/Closest function
N1 small 1.00 0.11 0.05 100 300 14.00 0.03 4.32 0.02 original network
14.00 0.03 4.60 0.02 euclidean distance
N1 large 1.00 0.13 0.00 1000 3996 67.00 0.00 28.11 0.00 original network
76.00 0.00 26.99 0.00 euclidean distance
N2 small 1.00 0.81 0.00 100 362 16.00 0.04 5.79 0.02 original
15.00 0.04 6.25 0.03 euclidean distance
N2 large 0.43 0.18 0.00 1000 4000 38.00 0.00 15.13 0.00 original network
50.00 0.00 17.14 0.00 euclidean distance
N3 small 0.00 0.11 0.00 100 200 6.00 0.02 2.25 0.12 original network
7.00 0.02 2.14 0.02 euclidean distance
N3 large 0.00 0.00 0.00 1000 3996 19.00 0.00 3.95 0.13 original
119.00 0.00 38.99 0.00 euclidean distance
  1. Instances where the null hypothesis (samples drawn from single distribution) cannot be rejected are marked with bold font, as well as scalar network descriptors such as diameter d or density ρ that are regenerated within ±10% margin of the original value. Metrics are described in Table 4.