From: Vadim Ogranovich <vograno_at_evafunds.com>

Date: Fri 06 May 2005 - 10:36:52 EST

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Fri May 06 10:43:53 2005

Date: Fri 06 May 2005 - 10:36:52 EST

Hi,

This is more of a general stat question. I am looking for a easily computable measure of a distance between two empirical distributions. Say I have two samples x and y drawn from X and Y. I want to compute a statistics rho(x,y) which is zero if X = Y and grows as X and Y become less similar.

Kullback-Leibler distance is the most "official" choice, however it needs estimation of the density. The estimation of the density requires one to choose a family of the distributions to fit from or to use some sort of non-parametric estimation. I have no intuition whether the resulting KL distance will be sensitive to the choice of the family of the distribution or of the fitting method.

Any suggestion of an alternative measure or insight into sensitivity of the KL distance will be highly appreciated.

The distributions I deal with are those of stock returns and qualitatively close to the normal dist with much fatter tails. The tails in general should be modeled non-parametrically.

Thanks,

Vadim

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R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Fri May 06 10:43:53 2005

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