Message-ID: <14095.37492.18515.147736@aragorn.ci.tuwien.ac.at>
Date: 1999-04-10T18:03:32Z
From: Kurt Hornik
Subject: KS test from ctest package
In-Reply-To: <Pine.GSO.4.05.9904090647350.28479-100000@auk.stats>
>>>>> Prof Brian D Ripley writes:
> On Thu, 8 Apr 1999, David Middleton wrote:
>>
>> This question is mainly aimed at Kurt Hornik as author of the ctest package,
>> but I'm cc'ing it to r-help as I suspect there will be other valuable
>> opinions out there.
>>
>> I have been attempting 2 sample Kolmogorov-Smirnov tests using the ks.test
>> function from the ctest package (ctest v.0.9-15, R v.0.63.3 win32). I am
>> comparing fish length-frequency distributions. My main reference for the KS
>> test at present is Sokal & Rohlf, Biometry (2nd edn), pages 440-445).
>>
>> The individuals in my samples are measured to the nearest 0.5cm and so in
>> most samples there are several identical length values. It appears that the
>> KS test statistic D is being overestimated (and the p value therefore
>> underestimated).
> If the data are discretized the KS test does not have the standard
> (distribution-free) distribution. `Distribution-free' here means
> independent samples from a continuous distribution. So the KS test is
> not IMHO appropriate in your problem. My view is that the function
> should warn you off, and not give a p-value if it finds ties. It might
> be good to construct the exact statistic, though.
The new version of ctest tries to be more intelligent about ties. It
gives a warning and hopefully also the right differences between the two
ecdfs.
Thanks,
-k
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