structural_consistency: Structural consistency of a network
In galanisl/LinkPrediction: Link prediction in complex networks

Description Usage Arguments Value Author(s) References Examples

Given a network of interest, it computes its Structural Consistency sigma_c. High values of sigma_c correlate with higher predictability of missing links in a network.

1	structural_consistency(g, p_H = 0.1, epochs = 100, k = NA)

`g`	igraph; The network of interest.
`p_H`	numeric; Fraction of network links to remove (perturbation set).
`epochs`	integer; Number of perturbation sets to consider.
`k`	integer; If k != NA and k < N (number of network nodes), the method is approximated by computing the k larget eigenvalues instead of all N.

A vector with epochs elements containing the consistency values for each perturbation set.

Gregorio Alanis-Lobato galanisl@uni-mainz.de

Lu, L. et al. (2015) Toward link predictability of complex networks. PNAS 112(8):2325-2330

# Compute the structural consistency of the Zachary Karate Club network
sigma_c <- structural_consistency(g = karate_club, p_H = 0.1, epochs = 100, 
              k = round(sqrt(igraph::vcount(karate_club))))
avg_sigma_c <- mean(sigma_c)