[R] Review process for new packages

[Duncan Murdoch]

Anupam Tyagi wrote:
> Hello,
>
> Duncan Murdoch <murdoch <at> stats.uwo.ca> writes:
>
>   
>> On 10/17/2006 2:22 AM, Andreas Wittmann wrote:
>>     
>>> Hi all, 
>>>
>>> i'm currently working on a creditmetrics package which includes functions
>>>       
> for computing the credit risk
>   
>> model creditmetrics. I guess it would be finished in a few days. 
>>     
>>> My question now is, does there exist some review process before sending it
>>>       
> to ctan or is it reviewed after
>   
>> having sended it?
>>
>> There's no review process to decide whether your package is useful or 
>> well-written.  If you want that kind of review you should submit it to 
>> the Journal of Statistical Software.
>>     
>
> Although, this is a sensitive issue, it is unfortunate that such review (or
> comment, if that is a more suitable word) process is not available at R. Is it
> possible to have some process where people can provide "comments", even if it is
> not a journal "review".

In a sense, that's what this mailing list does; there is also some 
information in CRAN task views.  If you ask "how do I...", you're likely 
to get recommendations for some packages and not others; that advice is 
worth listening to.

> It can help in improving the quality of packages
> submitted to R, in reducing bugs, or simply catching errors (coding and
> non-coding) that the author may have over-looked by mistake. Will contributing
> something to R, on provisional basis, and then asking for comments, and then
> submitting a final version work? 
>   

Essentially all contributions to CRAN are on a provisional basis:  
packages are updated frequently!  Getting a formal review of your 
contribution is harder, but you as author probably know people who would 
be qualified to give you comments and suggestions, and it would be worth 
asking them.  You as a package user should contribute positive 
suggestions to authors; most authors are happy to know that someone is 
interested in their work.
> It may also help to require the author to include a mathematical description of
> what has been submitted, if it is a statistical function. 
It would be pretty much impossible to automate this requirement, which 
means it would require a very large amount of human work.  Since this is 
what JSS does, why compete?  One thing you as author can do if you've 
got a JSS publication accepted, is to make sure that's clear on CRAN, 
e.g. by including the citation in the package description.

Duncan Murdoch
> This be because most
> new users find it difficult to read R code at the level of functions. They may
> also not be familiar with the statistical concept, but may know about it
> mathematically---because different disciplines have differentiated their
> specialized terminology (with some variation) as discipline specific statistical
> applications have evolved. I think this will make R more accessible to a wider
> user-base.