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 gmail.com>
- 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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- From: "Ernst H.K. Stelzer" <ernst.stelzer@physikalischebiologie.de>
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