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Re: [igraph] problems with parameters in barabasi.game()


From: Mario Lavezzi
Subject: Re: [igraph] problems with parameters in barabasi.game()
Date: Wed, 10 Sep 2008 16:22:19 +0200
User-agent: Thunderbird 2.0.0.16 (X11/20080724)

Hello Gabor
thank you so much.

I think I got confused by the different notation used in the papers I am considering at the moment.
It is still not the formula in the Dorogovtsev paper, though. I don't know why, maybe they don't consider multiple edges, or the results are only valid in some limit.
I think that things are a little different because, they actually allow multiple (directed) links, consider a parameter of "attractiveness" of a node which is only initial (and so it is not used at each time step as the "zero.appeal" value, as I understand).

One last question: can you suggest a quick way of generating degree sequences with a given power-law exponent to be used in the "degree.sequence.game"?
If you just want to have graphs with various power law degree distributions,
you might consider using 'degree.sequence.game', with method="vl", here
you can prescribe the exact degree distribution. It always generated connected graphs, but probably this is not a problem.

Thanks a lot!
best,
Mario

Best,
Gabor

On Mon, Sep 08, 2008 at 05:05:35PM +0200, Mario Lavezzi wrote:
Hello

I am trying to generate Scale-free graphs with barabasi.game()

What I want is an undirected graph for n agents, with neither loops, nor multiple edges.

I would like to generate different power-law distributions with different exponents (ALPHA) by manipulating the "a" coefficient in the formula (taken from the igraph documentation, page 18):

P[i] ~ k(i)^alpha + a

Since an exponent alpha different from 1 does not generate power laws, I keep it fixed at 1, so I work with:

P[i] ~ k(i) + a

_Example
_
What I write:
networkScFr =
barabasi.game(100000,directed=FALSE,out.pref=TRUE,power=1,zero.appeal=1,m=4)
networkScFrS = simplify(networkScFr, remove.multiple = TRUE,
remove.loops = TRUE)
power.law.fit(degScFr,xmin=10)
_What I get:_
power.law.fit(degScFr,xmin=10)

Call:
mle(minuslogl = mlogl, start = list(alpha = start))

Coefficients:
  alpha
2.970474


*_Question 1:
_*With zero.appeal = 1, I am considering

P[i] ~ k(i) + 1

which is not exactly the original BA model, which studied P[i] ~ k(i).
This is the extension proposed in http://arxiv.org/abs/cond-mat/0009090.
According to Dorogovstev et al, the power-law exponent should equal 2 + a/m, where m is the number of links added at each time step.
So, I should get ALPHA approx equal to 2.2, while I get ALPHA=2.97.
Am I correct? If not, where I am wrong?

*_Question 2:
_*I want to try with:

P[i] ~ k_i + 2

_What I write:_
networkScFr =
barabasi.game(n,directed=FALSE,out.pref=TRUE,power=1,zero.appeal=2,m=4)

_What I get:_

Warning message:
In barabasi.game(n, directed = FALSE, out.pref = TRUE, power = 1,  :
 `zero.appeal' is set to 1 for traditional BA game

Does this mean that the zero.appeal value is fixed at 1? How can I change it?

If I try to compute the exponent, I get:

power.law.fit(degScFr,xmin=10)
Call:
mle(minuslogl = mlogl, start = list(alpha = start))

Coefficients:
  alpha
3.042824

That is, I obtain ALPHA=3.04, while I expected ALPHA= 2+2/4 = 2.5.

Can anyone help?

Thanks!
Mario

--
Andrea Mario Lavezzi
Dipartimento di Studi su Politica, Diritto e Società
Università di Palermo
Piazza Bologni 8
90134 Palermo, Italy
tel. ++39 091 6625600
fax ++39 091 6112023
skype: lavezzimario
email: lavezzi (at) unipa.it
web: http://www.unipa.it/~lavezzi



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--
Andrea Mario Lavezzi
Dipartimento di Studi su Politica, Diritto e Società
Università di Palermo
Piazza Bologni 8
90134 Palermo, Italy
tel. ++39 091 6625600
fax ++39 091 6112023
skype: lavezzimario
email: lavezzi (at) unipa.it
web: http://www.unipa.it/~lavezzi





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