<p>The answer is, of course, "it depends", but I think you're asking about something different from what you think you're asking about.</p>

<p>I believe we can all agree that a question like</p>

<blockquote>
  <p>Is there an R package for fitting Random Forests?</p>
</blockquote>

<p>not only is off-topic but also shows a lack of research effort.</p>

<p>And likewise we can all agree that</p>

<blockquote>
  <p><code>randomForest::randomForest(...)</code> gives me an error. How can I fix it?</p>
</blockquote>

<p>is also off-topic, and at best belongs on StackOverflow.</p>

<p>Now consider a question like:</p>

<blockquote>
  <p>How do the <code>rpart</code> and <code>party</code> packages differ? Which one is preferred off-the-shelf for classification?</p>
</blockquote>

<p>I would say this question is a <strong>good question for CV</strong>, 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.</p>

<p>There might be a gray area here with a question like:</p>

<blockquote>
  <p>What is the difference between <code>caret</code> and <code>mlr</code>? How do they compare to <code>scikit-learn</code> in Python? What are the strengths and weaknesses of each?</p>
</blockquote>

<p>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. <em>(Note that this question would also probably be closed as "too broad", but I still think it gets the right idea across.)</em></p>

<p>Finally, on to a question that I hope captures the spirit of the one you linked to in the comments (<a href="https://stackoverflow.com/q/42022917/2954547">https://stackoverflow.com/q/42022917/2954547</a>):</p>

<blockquote>
  <p>What R package should I use for outlier detection?</p>
</blockquote>

<p>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</p>

<blockquote>
  <p>What are the current popular outlier detection techniques, and which of them are readily available in R?</p>
</blockquote>

<p>and that <strong>this would be on-topic here</strong>. 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:</p>

<blockquote>
  <p>Of the MCMC samplers available in R, which one should I use for this problem and why?</p>
</blockquote>

<p>which has more or less the same flavor.</p>
