Abstract Methodology extending nonparametric
goodness-of-fit tests to discrete null distributions
has existed for several decades. However,
modern statistical software has generally failed
to provide this methodology to users. We offer
a revision of R’s ks.test() function and a new
cvm.test() function that fill this need in the R
language for two of the most popular nonparametric
goodness-of-fit tests. This paper describes
these contributions and provides examples of
their usage. Particular attention is given to various
numerical issues that arise in their implementation