[R] Comparing distributions
Ralf B
ralf.bierig at gmail.com
Wed Jun 23 21:33:54 CEST 2010
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, nonnormal with multimodel shape (when
eyeballing 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 MannWhitney 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 eyeballing 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
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