You could request a bugzilla account and post it to
https://bugs.r-project.org/ yourself: from
https://www.r-project.org/bugs.html,
> In order to get a bugzilla account (i.e., become “member”), please
send an e-mail (from the address you want to use as your login) to
bug-report-requ...@r-project.org briefly explaining why, and a volunteer
will add you to R’s Bugzilla members.
(On the other hand, I think that posting to this list was a good idea
in any case, as it is more visible than the bugs list and may spark some
useful discussion.)
cheers
Ben Bolker
On 2023-12-11 9:44 a.m., tkp...@gmail.com wrote:
While using the Hodges Lehmann Mean in DescTools (DescTools::HodgesLehmann),
I found that it generated incorrect answers (see
<https://github.com/AndriSignorell/DescTools/issues/97>
https://github.com/AndriSignorell/DescTools/issues/97). The error is driven
by the existence of tied values forcing wilcox.test in Base R to switch to
an approximate algorithm that returns incorrect results - see
<https://aakinshin.net/posts/r-hodges-lehmann-problems/>
https://aakinshin.net/posts/r-hodges-lehmann-problems/ for a detailed
exposition of the issue.
Andri Signorell and Cyril Moser have a new C++ implementation of
DescTools::HodgesLehmann using a O(N log(N)) algorithm due to Monahan, but
wilcox.test in Base R appears to be still broken. Will someone kindly bring
this observation, as well as the existence of a solution, to the attention
of the relevant person(s) in the Base R development team?
The paper by Mohanan, as well as the original Fortran implementation of the
algorithm are linked to from
<https://github.com/AndriSignorell/DescTools/issues/97>
https://github.com/AndriSignorell/DescTools/issues/97). Inefficient O(N^2)
algorithms for the Hodges-Lehmann mean are known and are implemented in a
variety of packages. For example, the authors of rt.test
(https://cran.r-project.org/web/packages/rt.test) use the O(N^2) approach. I
suspect that Andri and Cyril will be more than happy to assist with fixing
wilcox.test in Base R with their implementation of Monahan's fast algorithm.
Sincerely
Thomas Philips
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