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Smoothhistogram and log-log scaling; Fitting of a power-law

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  • Subject: [mg130184] Smoothhistogram and log-log scaling; Fitting of a power-law
  • From: Stefano Ugliano <northerndream at>
  • Date: Mon, 18 Mar 2013 05:34:47 -0400 (EDT)
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Hi all again,

Two questions in one this time, I hope this won't create any confusion: although these questions sound pretty simple I haven't been able to answer them myself!

I am currently working on degree distributions on networks, and

1) I need to produce histograms of these degrees (a list of positive integers) vs their frequency. Their distribution often follows a power law, so that I am required to scale these histograms in a log-log scale.

The problem is: I really love SmoothHistogram for the clarity of its output and for automatically normalising everything, but so far I have not managed to do the log-log scaling in it, which is instead pretty straightforward with a normal Histogram... Is there any solution that joins the two worlds profitably?

2) Finally, it is important to find the "slope" of the (log-scaled) distribution, i.e. the exponent of the distribution itself. I am still not really used to fit non-polynomial functions, and I'm quite confused by the many possible approaches, which is in your opinion the best (=simpler and tidier=) way to proceed?

Thank you all.

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