From: l y <pligly_at_gmail.com>

Date: Mon, 07 Jul 2008 11:44:16 +0800

R-help_at_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. Received on Mon 07 Jul 2008 - 03:54:15 GMT

Date: Mon, 07 Jul 2008 11:44:16 +0800

Hi everyone, when I use the two sample Kolmogorov¨CSmirnov ks2Test like this:
x=read.table("e:/x.txt")

y=rstable(1000,alpha,beta,gamma,delta)

I alway get results as follows:

Warning messages:

1: In ks.test(x = x, y = y, alternative = "two.sided") :
cannot compute correct p-values with ties
2: In ks.test(x = x, y = y, exact = TRUE, alternative = "two.sided") :
cannot compute correct p-values with ties
3: In ks.test(x = x, y = y, alternative = "less") :
cannot compute correct p-values with ties
4: In ks.test(x = x, y = y, alternative = "greater") :
cannot compute correct p-values with ties
I know that the one-sample Kolmogorov¨CSmirnov test only applied to
continuous distributions, does the two-sample ks test require this? Even if
it requires, the stable distribution is continuous.
So I also tried this:

x=read.table("e:/x.txt");

y=rnorm(1000,mean,sd);

ks2Test(x,y);

And this:

x=read.table("e:/x.txt");

ks.test(x,"norm");

Strangely,I got a total same result! I really want to know whether there are
any other sources that could induce this result except for the continuity
of distribution? If there are, what are they?
Any help will be much appreciated!

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