From: Don MacQueen <macq_at_llnl.gov>

Date: Sat 04 Feb 2006 - 02:25:42 EST

Date: Sat 04 Feb 2006 - 02:25:42 EST

7 repetitions is not nearly enough to get a good estimate of the
variability of the test statistic.

Try this:

nrep <- 500

pvals <- tstvals <- numeric(nrep)

for (i in seq(nrep)) {

tmp <- ks.test(rexp(2500,0.4),"pexp",0.4)
pvals[i] <- tmp$p.value

tstvals[i] <- tmp$statistic

}

hist(pvals)

hist(tstvals)

round(quantile(pvals,pr=seq(0.05,.95,.05)),2)

At 2:36 PM +0000 2/3/06, Emanuele Mazzola wrote:

>Hi everybody,

*>
**>while performing ks.test for a standard exponential distribution on samples
**>of dimension 2500, generated everytime as new, i had this strange behaviour:
**>
**>>data<-rexp(2500,0.4)
**>>ks.test(data,"pexp",0.4)
**>
**> One-sample Kolmogorov-Smirnov test
**>
**>data: data
**>D = 0.0147, p-value = 0.6549
**>alternative hypothesis: two.sided
**>
**>>data<-rexp(2500,0.4)
**>>ks.test(data,"pexp",0.4)
**>
**> One-sample Kolmogorov-Smirnov test
**>
**>data: data
**>D = 0.019, p-value = 0.3305
**>alternative hypothesis: two.sided
**>
**>>data<-rexp(2500,0.4)
**>>ks.test(data,"pexp",0.4)
**>
**> One-sample Kolmogorov-Smirnov test
**>
**>data: data
**>D = 0.0171, p-value = 0.4580
**>alternative hypothesis: two.sided
**>
**>>data<-rexp(2500,0.4)
**>>ks.test(data,"pexp",0.4)
**>
**> One-sample Kolmogorov-Smirnov test
**>
**>data: data
**>D = 0.0143, p-value = 0.6841
**>alternative hypothesis: two.sided
**>
**>>data<-rexp(2500,0.4)
**>>ks.test(data,"pexp",0.4)
**>
**> One-sample Kolmogorov-Smirnov test
**>
**>data: data
**>D = 0.0145, p-value = 0.6684
**>alternative hypothesis: two.sided
**>
**>>data<-rexp(2500,0.4)
**>>ks.test(data,"pexp",0.4)
**>
**> One-sample Kolmogorov-Smirnov test
**>
**>data: data
**>D = 0.0123, p-value = 0.8435
**>alternative hypothesis: two.sided
**>
**> >data<-rexp(2500,0.4)
**>>ks.test(data,"pexp",0.4)
**>
**> One-sample Kolmogorov-Smirnov test
**>
**>data: data
**>D = 0.0186, p-value = 0.3532
**>alternative hypothesis: two.sided
**>
**>
**>It seems kind of strange to me that max p-value obtained is 0.8435 and all
**>the best i can have from the rest is a 0.66-0.68.
**>I'm probably not so expert in running this kind of test, but am I doing
**>something wrong?
**>I would expect p values ranging from 0.75 (to be kind) to 0.9, 0.95. How is
**>this possible?
**>
**>Thank you in advance for your answers.
**>See you soon
**>EM
**>
**>______________________________________________
**>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
*

-- -------------------------------------- Don MacQueen Environmental Protection Department Lawrence Livermore National Laboratory Livermore, CA, USA ______________________________________________ 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.htmlReceived on Sat Feb 04 02:39:42 2006

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