[R] ks.test - continuous vs discrete

Peter Flom flom at ndri.org
Thu Mar 28 17:33:57 CET 2002

>>> David Middleton <dmiddleton at fisheries.gov.fk> 03/28/02 05:48AM >>>


> > I frequently want to test for differences between animal size
>>frequency  distributions.  The obvious test (I think) to use is the
>> Kolmogorov-Smirnov  two sample test (provided in R as the function >>ks.test in package ctest).

and later added:

>Apologies for my vague description.  The Wilcoxon rank sum test is a test >of difference in location, as is the permutation test I believe.  I am
>interested in more than just location - the animal size distributions I have
>in mind are often multimodal, encompassing different cohorts for example >- so I am interested in a more general test of differences in the
>distributions, both for exploratory purposes and too see if it is
>appropriate to lump samples.  Thus the KS test seems the "obvious" >choice.

In which case, I recommend the methods developed and advocated  Handcock & Morris 



For which code in R is available.

These provide more complete methods for comparing two distributions; I think they're really good.  The only caveat is that the sample size should be large (at least hundreds, preferably thousands).


Peter L. Flom, PhD
Assistant Director, Statistics and Data Analysis Core
Center for Drug Use and HIV Research
National Development and Research Institutes
71 W. 23rd St
New York, NY 10010
(212) 845-4485 (voice)
(917) 438-0894 (fax)

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