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

From: Daniele Capocefalo
Subject: Re: [igraph] Understanding Barabasi Function and how to simulate a scale free()
Date: Mon, 8 May 2017 11:14:23 +0200
User-agent: Mozilla/5.0 (X11; Linux x86_64; rv:45.0) Gecko/20100101 Thunderbird/45.8.0

I see now! Thanks for your help!


On 04/05/17 15:24, Tamas Nepusz wrote:
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

That's much closer.


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Daniele Capocefalo
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