R version 3.1.3 RC (2015-03-01 r67921) -- "Smooth Sidewalk"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-unknown-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> ## some examples of the KS test
> 
> ## unrealistic one of PR#14561
> ds1 <- c(1.7,2,3,3,4,4,5,5,6,6)
> ks.test(ds1, "pnorm", mean = 3.3, sd = 1.55216)

	One-sample Kolmogorov-Smirnov test

data:  ds1
D = 0.274, p-value = 0.4407
alternative hypothesis: two-sided

Warning message:
In ks.test(ds1, "pnorm", mean = 3.3, sd = 1.55216) :
  ties should not be present for the Kolmogorov-Smirnov test
> # how on earth can sigma = 1.55216 be known?
> 
> # R >= 2.14.0 allows the equally invalid
> ks.test(ds1, "pnorm", mean = 3.3, sd = 1.55216, exact = TRUE)

	One-sample Kolmogorov-Smirnov test

data:  ds1
D = 0.274, p-value = 0.3715
alternative hypothesis: two-sided

Warning message:
In ks.test(ds1, "pnorm", mean = 3.3, sd = 1.55216, exact = TRUE) :
  ties should not be present for the Kolmogorov-Smirnov test
> 
> ## Try out the effects of rounding
> set.seed(123)
> ds2 <- rnorm(1000)
> ks.test(ds2, "pnorm") # exact = FALSE is default for n = 1000

	One-sample Kolmogorov-Smirnov test

data:  ds2
D = 0.0194, p-value = 0.8452
alternative hypothesis: two-sided

> ks.test(ds2, "pnorm", exact = TRUE)

	One-sample Kolmogorov-Smirnov test

data:  ds2
D = 0.0194, p-value = 0.8379
alternative hypothesis: two-sided

> ## next two are still close
> ks.test(round(ds2, 2), "pnorm")

	One-sample Kolmogorov-Smirnov test

data:  round(ds2, 2)
D = 0.0192, p-value = 0.856
alternative hypothesis: two-sided

Warning message:
In ks.test(round(ds2, 2), "pnorm") :
  ties should not be present for the Kolmogorov-Smirnov test
> ks.test(round(ds2, 2), "pnorm", exact = TRUE)

	One-sample Kolmogorov-Smirnov test

data:  round(ds2, 2)
D = 0.0192, p-value = 0.8489
alternative hypothesis: two-sided

Warning message:
In ks.test(round(ds2, 2), "pnorm", exact = TRUE) :
  ties should not be present for the Kolmogorov-Smirnov test
> # now D has doubled, but p-values remain similar (if very different from ds2)
> ks.test(round(ds2, 1), "pnorm")

	One-sample Kolmogorov-Smirnov test

data:  round(ds2, 1)
D = 0.0367, p-value = 0.1344
alternative hypothesis: two-sided

Warning message:
In ks.test(round(ds2, 1), "pnorm") :
  ties should not be present for the Kolmogorov-Smirnov test
> ks.test(round(ds2, 1), "pnorm", exact = TRUE)

	One-sample Kolmogorov-Smirnov test

data:  round(ds2, 1)
D = 0.0367, p-value = 0.1311
alternative hypothesis: two-sided

Warning message:
In ks.test(round(ds2, 1), "pnorm", exact = TRUE) :
  ties should not be present for the Kolmogorov-Smirnov test
> 
> 
> proc.time()
   user  system elapsed 
  0.127   0.011   0.133