Questions about R packages are off-topic on SO, and since programming questions are off-topic on CV, a fortiori packages questions, which are about programming (in R) are off-topic on CV. That's why I always ask questions on algorithms (on SO), even if I often would much rather be pointed to a package. However, learning about packages is an integral part of doing statistics with R. Is there somewhere on Stack Exchange where I can ask question about which R package to use for a specific statistical inference problem? If not, as you guys are statistical experts, and many of you use/have used R, where do you go when you need advice about packages? Other than the R-help mailing list.
The answer is, of course, "it depends", but I think you're asking about something different from what you think you're asking about.
I believe we can all agree that a question like
Is there an R package for fitting Random Forests?
not only is off-topic but also shows a lack of research effort.
And likewise we can all agree that
randomForest::randomForest(...)gives me an error. How can I fix it?
is also off-topic, and at best belongs on StackOverflow.
Now consider a question like:
How do the
partypackages differ? Which one is preferred off-the-shelf for classification?
I would say this question is a good question for CV, because while, yes, its focus is restricted to R packages, it is actually a question about statistical computing. It is not about programming as such (i.e. it doesn't belong on StackOverflow), and while it is asking for a software recommendation I would say it's still topical enough to not kick it over to SoftwareRecs, where I imagine there is much less domain expertise floating around anyway.
There might be a gray area here with a question like:
What is the difference between
mlr? How do they compare to
scikit-learnin Python? What are the strengths and weaknesses of each?
because it's not really about statistical computing. But I (as an opinionated poster without moderator privileges) would still say it's on-topic, because it's about statistics-specific methods and workflows. (Note that this question would also probably be closed as "too broad", but I still think it gets the right idea across.)
Finally, on to a question that I hope captures the spirit of the one you linked to in the comments (https://stackoverflow.com/q/42022917/2954547):
What R package should I use for outlier detection?
As stated, this question would rightfully be closed as either "opinion-based" or "too broad". But what is the question really trying to ask? I would argue that the question could have been phrased as
What are the current popular outlier detection techniques, and which of them are readily available in R?
and that this would be on-topic here. The question isn't really about R, it's about statistical modeling, with an added requirement that the model have an R implementation. This, I think, is what you are asking in your question on StackOverflow:
Of the MCMC samplers available in R, which one should I use for this problem and why?
which has more or less the same flavor.
Not arguing that ssdecontrol has an excellent answer, but as someone who is very interested in R packages, I find that subscribing to R-bloggers is really, really, useful. It will keep you in touch with what is new in the R package world as well as linking to blogs describing the use of various R packages.