On 09/25/2010 03:23 PM, Rainer M Krug wrote:
Evaluate, for me, does not necessary mean "test if they are significantly different", but rather to quantify the difference. If that is what you are looking for, you could look at the "Earth Movers Distance", where a package is available at R-forge (https://r-forge.r-project.org/projects/earthmovdist/) which I co-wrote and used before. Cheers, Rainer
Thanks Rainer. I had a quick look at wikipedia and the package you mention, and it seems what I am looking for. Just a question about normalization of the distance calculated by the algorithm. Let us say that I have 4 distributions A,B,C,D coupled this way (A,B) and (C,D). The length of data in A is equal to the length of data in B, same applies to C and D but length(A)!=length(C). Now, the argument I would like to make is that A and B are more similar than C and D and show a couple of numbers to prove this. Bottom line: provided my data lists are long enough, does this distance scale with the number of data? and if they do, how should I normalize this distance to compare the results?
Cheers Lorenzo ______________________________________________ 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.
