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: > From: S. Nunes <[EMAIL PROTECTED]> > Subject: [R] Measuring dispersion > To: [EMAIL PROTECTED] > Received: Tuesday, 17 June, 2008, 7:56 PM > Hi, > > I'm looking for a function to measure the dispersion of > a set of > values ranging from 0 to 1. > This function should be 0 if all the values are evenly > spaced within > the interval and it should be > 0 if values are > clustered. > The more clustered the values are, the higher should the > function be. > > An example: > > [0; 0.2; 0.4; 0.6; 0.8; 1] - function should be ~ 0 > [0; 0.1; 0.1; 0.15; 1] - function should be > 1 > > This data comes from time-dependent observations recorded > between a > start time (0) and an end time (1). > I want to find out which series are more clustered, i.e. > less evenly > distributed. > > I'm going to test Kurtosis for this but it doesn't > seem to be the best > tool for the job. > As I understand, Kurtosis evaluates the > "strength" of a single central > peak. My data can have multiple peaks (clusters). > > Thanks in advance for your comments, > -- > Sérgio Nunes > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, > reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
