Fig 1.
This example with parameters of (n = 1,000, K = 8, p = 0.04), generated in Mathematica 10 by Wolfram Research, has CC = 0.6170 and DS = 4.1531. Nodes are distinguished by different sizes and colors representing their degrees ranging from from 13 to 19.
Fig 2.
Distributions of degrees in a Watts-Strogatz network and degrees estimated by Eq (6).
The WS network was generated with parameters of (n = 1,000, K = 8, p = 0.04).
Fig 3.
1,000 WS networks were randomly generated with parameters of (n = 1000, K = 8, p = 0.04).
Fig 4.
Estimated values of p, CC and DS.
For each case of (a) n = 10,000 and (b) n = 20,000, 100 WS networks were generated with K = 80 and a randomly chosen p ∈ [0.005, 0.05]. From each network, s = 100 nodes were randomly sampled along with their degrees to calculate from Algorithm 1. All estimated values were normalized between 0 and 1.
Fig 5.
Sample means and 95% confidence intervals of 30 ratios of .
For each combination of n = 10,000, 20,000, K = 80 and s/n = 1%, 3%, 5%, 30 WS networks were generated with a randomly chosen p ∈ [0.05, 0.2]. For each network, the value of was calculated from Algorithm 1.
Table 1.
Sample means and 95% confidence intervals of 30 ratios of .