R devel - Jun 2001 - KS test in R.1.3.0 has incorrect p-values. (PR#1004)

Based on a report to the Windows maintainers from Richard Rowe
<Richard.Rowe@jcu.edu.au>:

NEWS for 1.3.0 says

    o   Exact p-values are available for the two-sided two-sample
        Kolmogorov-Smirnov test.

I think the (new) p-values are computed but are backwards:
> set.seed(123)
> x <- rnorm(50)
> y <- runif(50)
> ks.test(x,y, exact=T)$p
[1] 1
> 1 - ks.test(x,y, exact=T)$p
[1] 4.047605e-08
> ks.test(x,y, exact=F)$p
[1] 3.099506e-07
> y<-rnorm(50)
> ks.test(x,y, exact=T)$p
[1] 0.02015456
> ks.test(x,y, exact=F)$p
[1] 0.9971923

I'll commit the obvious fix unless anyone knows better.  Neither value
agrees well with S-PLUS 6, which gives
> source("dumpdata.R")
> ks.gof(x, y)$p
[1] 1.453458e-07


-- 
Brian D. Ripley,                  ripley@stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595



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>>>>> ripley  writes:
> Based on a report to the Windows maintainers from Richard Rowe
> <Richard.Rowe@jcu.edu.au>:
> NEWS for 1.3.0 says
>     o   Exact p-values are available for the two-sided two-sample
>         Kolmogorov-Smirnov test.
> I think the (new) p-values are computed but are backwards:
>> set.seed(123)
>> x <- rnorm(50)
>> y <- runif(50)
>> ks.test(x,y, exact=T)$p
> [1] 1
>> 1 - ks.test(x,y, exact=T)$p
> [1] 4.047605e-08
>> ks.test(x,y, exact=F)$p
> [1] 3.099506e-07
>> y<-rnorm(50)
>> ks.test(x,y, exact=T)$p
> [1] 0.02015456
>> ks.test(x,y, exact=F)$p
> [1] 0.9971923
> I'll commit the obvious fix unless anyone knows better.
Thanks for doing.  I had received a similar private bug report but had
not gotten to fixing this.
> Neither value agrees well with S-PLUS 6, which gives
>> source("dumpdata.R")
>> ks.gof(x, y)$p
> [1] 1.453458e-07
Strange because the underlying algorithm should be the same.  Have you
tried R vs Splus on larger samples (say, 100 each)?

-k
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