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Re: Small World Network model random data generation

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  Re: Small World Network model random data generation Dennis Lee Bieber <wlfraed@ix.netcom.com> - 2014-08-26 09:23 -0400

#77039 — Re: Small World Network model random data generation

On Tue, 26 Aug 2014 12:16:33 +0200, lavanya addepalli <phani.lav@gmail.com>
declaimed the following:

>How can i generate a random data that is identical to my realworld data
>

	By definition, "random data" will be unlikely to ever be "identical" to
your "realworld data".


>i am supposed to refer the attached paper
>
>Real Data
>
>node pairs and the time they spend together connected
>
>node node time in seconds
>4391 2814 16.0
>4945 3545 386.0
>5045 4921 63078.0
>5045 3545 896.0
>4921 3545 896.0
>5045 1683 1108.0
>4921 1683 1108.0
>5454 4391 4161.0
>5454 5070 2755.0
>5070 4391 2935.0
>1158 305 1.0
>5045 3140 48767.0
>4921 3140 58405.0
>5372 2684 460.0
>1885 1158 351.0
>1349 1174 6375.0
>

	Since I see no cases of duplicate node /pairs/ it is difficult to
figure out just what that data really represents...

	With enough data, with duplicate pairs having different times, I'd
likely group by pairs, generate mean and standard deviation for the times
of the matching pairs, then generate some count of the pairs to develop
weights... Finally, using the weights I'd attempt to generate random node
pairs and then use the mean/SD of the result pair to generate a time from
the gaussian distribution.

	With only the data you have, I'd end up with a sparse 2D matrix
M[first_node, second_node] = time

	And then selecting random samples from that...
-- 
	Wulfraed                 Dennis Lee Bieber         AF6VN
    wlfraed@ix.netcom.com    HTTP://wlfraed.home.netcom.com/

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