[R] about power.law.fit

2009-01-18 Thread Weijia You
Dear all,

I'm using igraph for some analysis about the network I have. I have a
question about the function power.law.fit.

I wonder if there is any test for checking whether the  power.law.fit is
good for the input, i.e., under which situation, could we use this function
to get a reliable result. I'm afraid even I input a random graph without any
property of power-law characteristics, it will returns an outcome which
seems to be a fit to available data while it has no meaning to us. Is there
any index like goodness of fit ?

Thank you for any comments.

Best!
Weijia

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[R] how to get degree according to the name of the node?

2008-12-28 Thread Weijia You
Hi all,

I have two networks for the same group of the users.
I want to compare individual's degree in different networks.
But how could I get the degrere of the nodes according to its name?

When I use degree(g1), I could only get a vector of the degree of each node.
But when I turn to g2, I don't know whose degree it is so I can't match it
with the degree(g2).

Now I'm trying to make the users appearing in the edgelist in the same
sequence.
for example:
in g1 input file
A B  1
C D  2
C B  3

in g2 input file
 A B  0
C D  12
C B  0

If I make the two input file like this, will it help? I mean the degree
vector will be exactly the same in the two graph?

Thanks!

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[R] question about Assortative and Disassortative Mixing

2008-12-27 Thread Weijia You
Dear colleagues,

I'm trying to have a look at the Assortative and Disassortative(
http://en.wikipedia.org/wiki/Assortative_mixing) of the network I have.
But it seems that the igraph hasn't mentioned that yet.

I have to get the in/out degree of the vertices of each edge and calculate
the Pearson's Correlation coefficient which seems to be quite a huge task
for me. :(

So I wonder if anyone had done that before and give me some hints on it?

Thank you in anticipation!

Weijia

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[R] question about SNA in R, thanks!

2008-12-27 Thread Weijia You
Dear colleagues,

I'm trying to have a look at the Assortative and Disassortative (
http://en.wikipedia.org/wiki/Assortative_mixing) of the network I have.
But it seems that the igraph hasn't mentioned that yet.

I have to get the in/out degree of the vertices of each edge and calculate
the Pearson's Correlation coefficient which seems to be quite a huge task
for me. :(

So I wonder if anyone had done that before and give me some hints on it?

Thank you in anticipation!

Weijia

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and provide commented, minimal, self-contained, reproducible code.


[R] about qqmath, thanks!

2008-12-06 Thread Weijia You
Dear collegues,

Is there anyone who ever used qqmath().

Actually, I want to know the distribution of the dependent varible.
It's a count number, so it should be poisson or negative binomial
distribution.
But how could I use R to get the  ë and á? Or to demonstrate the
distribution to be negative binomial ?

I tried my best to find the examples by google, but failed.

Thank you for the suggestions.

Best!

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[R] about centralization

2008-11-30 Thread Weijia You
Hi all,

Is there anyone who ever used igraph to calculate the index of
centralization ?
I tried my best but can't find it in igraph.

The brief introduction to centralization can be found here , and I think
it's an important index for measuring the centrality on the aggregated
level.(http://faculty.ucr.edu/~hanneman/nettext/C10_Centrality.html)

Thank you for any comments and suggestions.

Best wishes!

Weijia

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Re: [R] Welcome to the R-help mailing list (Digest mode)

2008-11-27 Thread Weijia You
Hi friends,

Is there anyone who happened to import data set in the DL format into R
for further analysis?

In the package of network, there's only a method named read.paj().
So now, I have to get the dl file from the original data set, and use UCINET
to convert it to .net file. It's too complicated.
:(

In the package of igraph, edgelist is one the format which can be
imported, however, weight can not be expressed. As for the format ncol,
weight is considered, but it's always undirected.

Thank you for comments and suggestions!

Best!

Weijia

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and provide commented, minimal, self-contained, reproducible code.