Re: [igraph] estimating parameters for use in a barasi game

[Gábor Csárdi]

Hi Jesse,

some more minor comments below.

On Mon, Apr 6, 2009 at 11:51 AM, Tamas Nepusz <address@hidden> wrote:
> Hi Jesse,
>
>> I have some empirical networks that I need to use as a basis for a
>> monte-carlo simulation.  I need to generate new networks that have
>> similar characteristics to the current networks (i.e. matched on
>> density, in and out degree distributions).  The empirical networks
>> exhibit preferential attachment, so I am using the "barabasi.game"
>> functions to generate the networks in R, but I am having a hard time
>> getting the input parameters right so the degree distributions of the
>> empirical and generated networks are consistent
> I think it's really hard to achieve that even if your original network
> exhibits preferential attachment. I would try a different approach, drop
> the assumption of the network being a Barabasi-Albert network and simply
> generate my simulated networks using degree.sequence.game (in R) or
> Graph.Degree_Sequence (in Python) with the Viger-Latapy sampling method.

I think this actually uses Monte-Carlo, but I might be wrong. (Anyway,
check the paper if you are interested.) Another method that uses
Monte-Carlo to sample networks uniformly is described here:
http://arxiv.org/abs/cond-mat/0312028

> This method is said to sample uniformly from the space of networks
> having the same in- and out-degree distribution.

Actually, it is not just said, it has been proven. :)

Gabor

> Another way to go is to
> take your original network and rewire it while preserving the degree
> distribution; this is implemented in rewire (in R) or Graph.rewire (in
> Python). Of course you will have to use a large number of rewiring
> iterations to make your resulting simulated graph more or less
> independent from your original.
>
> --
> Tamas
>
>
> _______________________________________________
> igraph-help mailing list
> address@hidden
> http://lists.nongnu.org/mailman/listinfo/igraph-help
>



-- 
Gabor Csardi <address@hidden>     UNIL DGM