John, thanks for starting (or restarting) this thread.? I'd like to
add to the discussion with another concrete example, about as simple
as it gets, which may help focus at least part of this discussion.
I have worked with Taylor Arnold to implement a method developed in
Conover (1972) for Kolmogorov-Smirnov goodness-of-fit tests for
discrete distributions (one-sample only).? We needed this for an
applied problem.? It seemed to be a natural extension to
stats::ks.test(), so we modified that code (commenting every addition
very carefully) and modifying ks.test.Rd in parallel (and with
commenting).? For convenience, we put this in a package ks.test that
is on R-Forge but not submitted to CRAN.? We've written a short paper
about this (and also implemented similar Cramer-von Mises tests in
package cvm.test).
1. I think the cvm.test function/package is suitable for CRAN (rather,
I can't make a compelling argument it should be added to the base
distribution).? It doesn't directly extend anything in the base R
distribution at the moment (at least, to my knowledge).
2. I think it would be ideal for stats::ks.test() to be updated using
the new ks.test.R and ks.test.Rd. I'll spare you the longer argument,
but there are simple examples of a "bug" (quotes intended, because it
surrounds non-intended functionality with discrete distributions) in
stats::ks.test().
3. Finally, I note the presence of a <FIXME> in stats::ks.test() that
looks rather straightforward.? I'd be happy to do this <FIXME> as part
of this contribution (though perhaps I should read the cited paper and
conduct some simple simulations). A simple, "that would be great,
Jay" or "don't bother" would suffice -- it may be that
someone else is
working on it.
Thoughts welcome, either on these particular issues, or on the manner
in which they relate to John's thread.
Cheers,
Jay
--
John W. Emerson (Jay)
Associate Professor of Statistics
Department of Statistics
Yale University
http://www.stat.yale.edu/~jay
