   Check out the KL divergence test
http://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence 
<http://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence>

@tommychheng
Programmer and UC Irvine Graduate Student
Find a great grad school based on research interests: http://gradschoolnow.com


On 6/23/10 12:33 PM, Ralf B wrote:
> I am trying to do something in R and would appreciate a push into the
> right direction. I hope some of you experts can help.
>
> I have two distributions obtrained from 10000 datapoints each (about
> 10000 datapoints each, non-normal with multi-model shape (when
> eye-balling densities) but other then that I know little about its
> distribution). When plotting the two distributions together I can see
> that the two densities are alike with a certain distance to each other
> (e.g. 50 units on the X axis). I tried to plot a simplified picture of
> the density plot below:
>
>
>
>
> |
> |                                                         *
> |                                                      *     *
> |                                                   *    +   *
> |                                              *     +     +  *
> |                     *        +           *   +            +  *
> |                 *        +*     +   *  +                   + *
> |              *       +       *     +                           +*
> |           *       +                                               +*
> |        *       +                                                    +*
> |     *      +                                                          + *
> |  *      +                                                               + *
> |___________________________________________________________________
>
>
> What I would like to do is to formally test their similarity or
> otherwise measure it more reliably than just showing and discussing a
> plot. Is there a general approach other then using a Mann-Whitney test
> which is very strict and seems to assume a perfect match. Is there a
> test that takes in a certain 'band' (e.g. 50,100, 150 units on X) or
> are there any other similarity measures that could give me a statistic
> about how close these two distributions are to each other ? All I can
> say from eye-balling is that they seem to follow each other and it
> appears that one distribution is shifted by a amount from the other.
> Any ideas?
>
> Ralf
>
> ______________________________________________
> 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.

	[[alternative HTML version deleted]]

