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. 2018 Jun 21;13(6):e0198525. doi: 10.1371/journal.pone.0198525

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© 2018 Ali et al

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Fig 2 — Showing the Degree distribution i.e P(k) vs. k graph, After Knock out experiment at 0, 10, 20, 30, 40, 50, 100 nodes removal and it is also fitted to the power law with exponent γ falling in range of Characteristic Heirarchial Networks i.e. (0 ≤ γ ≤ 2); Showing the Clustering Co-efficient i.e C(k) vs. k graph; After Knock out experiment at 0, 10, 20, 30, 40, 50, 100 nodes removal and it is also fitted to the power law with exponent α falling in range of Characteristic Heirarchial Networks i.e. (α ~ 1); Showing the Avg Neibourhood Connectivity i.e Cn(k) vs. k graph; After Knock out experiment at 0, 10, 20, 30, 40, 50, 100 nodes removal and it is also fitted to the power law with exponent β falling in range of Characteristic Heirarchial Networks i.e. (β ≤ 1), Showing the Betweeness Centrality, Closeness Centrality and Eigenvector Centrality i.e C_b, C_c and C_e vs. k graph respectively, After Knock out experiment at 0, 10, 20, 30, 40, 50, 100 nodes removal and it is also fitted to the power law with exponent ϵ, δ and μ in order.