R devel - Dec 2023 - Base R wilcox.test gives incorrect answers, has been fixed in DescTools, solution can likely be ported to Base R

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

 


	[[alternative HTML version deleted]]

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-request at 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., tkpmep at 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
> 
>   
> 
> 
> 	[[alternative HTML version deleted]]
> 
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