# [Rd] ks.test in ctest package (PR#934)

**Kurt Hornik
**
Kurt.Hornik@ci.tuwien.ac.at

*Sun, 13 May 2001 18:39:26 +0200*

>>>>>* mh smith writes:
*
>* 1. There is, I believe, some redundant code in the calculation of the
*>* test statistic in ks.test in the package ctest.
*
Thanks, fixed.
>* 2. The manual entry should also make it clear that the one-sided
*>* tests are not about theactual cdf in relation to the null hypothsis cdf
*>* Fo, but about the quantiles of the actual distribution in relation to
*>* the quantiles of the null hypothesis cdf.
*
>* ...
*
THanks for catching this bug. This should really give the usual
behavior that e.g. `alternative = "less"' means H_0: F >= F_0 for all
points vs H_a: F(t) < F_0(t) for some t. Fixed now.
>* 3. Another feature that it would be very useful to add to ks.test
*>* would be the automatic return of a confidence interval for the actual
*>* cdf F. Adding a conf.level argument and taking the form of the interval
*>* from the value of the alternative argument would be a relatively simple
*>* task, although it would require . This would bring the value of the
*>* function into line with the t.test function.
*
I am not sure whether we want to do this in the simple htest framework.
Attempting to print a confidence interval given by two functions rather
than two values will be confusing. I'd much rather have users do
confint(ecdf(x), conf.level = 0.95)
where a generic confint as in MASS with a method for objects of class
"ecdf" as in stepfun.
[The ``classical'' tests conceptually are really about a single
parameter only. Should this be changed? One could argue that if a
hypothesis about the underlying distribution function is tested ...]
-k
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