Re: [igraph] Understanding Barabasi Function and how to simulate a scale free()

[Tamas Nepusz]

varies consistenyl. As of an example, I'll post here the results obtained using a network of 84 nodes and 221 edges and an alpha estimated on 2.614071596

 

That's too small a network to make any meaningful estimation of an exponent. At small sample sizes, power laws, exponential distributions and many other distributions are practically indistinguishable from each other. Also, when testing, turn off the finite size correction:

>>> g=Graph.Static_Power_Law(n=100000, m=250000, exponent_out=2.61407159636724, multiple=False, loops=False, finite_size_correction=False)

>>> power_law_fit(g.degree()).alpha

2.677378126993507

That's much closer.

T.