Hi everyone, when I use the two sample Kolmogorov–Smirnov 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–Smirnov 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!

Lily

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