On Wed, Jun 18, 2008 at 12:10:18AM +0100, S. Nunes wrote:
> Thanks for the suggestion, however I'm looking for a score since my
> goal is to rank thousands of distributions.
> For instance, given a large text, I would like to rank all terms
> according to their distribution (dispersion) within the text.
>
> Terms evenly distributed in the text should have a low score. Terms
> following an uneven distribution should rank higher.
as a perhaps rather rough-and-ready approach, you could look at
the variance of the difference series, considering your example:
> Thanks again,
> --
> S?rgio Nunes
>
> 2008/6/17 Moshe Olshansky <[EMAIL PROTECTED]>:
> > You could also look at the difference between your empirical distribution
> > and the uniform distribution (something like Kolmogorov-Smirnov test).
> >
> >
> > --- On Tue, 17/6/08, S. Nunes <[EMAIL PROTECTED]> wrote:
[...]
> >> An example:
> >>
> >> [0; 0.2; 0.4; 0.6; 0.8; 1] - function should be ~ 0
> var(diff(c(0, 0.2, 0.4, 0.6, 0.8, 1)))
[1] 2.311116e-33
(that's 0 obviously, with some error due to floating point processing)
> >> [0; 0.1; 0.1; 0.15; 1] - function should be > 1
> var(diff(c(0, 0.1, 0.1, 0.15, 1)))
[1] 0.1616667
Best regards, Jan
--
+- Jan T. Kim -------------------------------------------------------+
| email: [EMAIL PROTECTED] |
| WWW: http://www.cmp.uea.ac.uk/people/jtk |
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