My exact thought. R has great tools but the language is wonky. That's not a dig against them. It wasn't designed by language designers. However, its interactive nature is great for data scientists. So it seems like Clojure (possibly Scala) is a better fit than Java.
it isn't the R syntax, as a language, it is rather the package ecosystem and the invested resources it encapsulates.
The ecosystem didnt come into existence by magic. The early adopters did have a choice into which language to invest their time. Obviously the R syntax alone was enough of an incentive to starts building useful libraries in it, instead of lisp, python, etc.
I'm confused. Are you saying that the package ecosystem is what makes R attractive, or that it's what makes it inscrutable?
I'm sure he's saying that package ecosystem is what makes R attractive.
I'd need to dig into the source code of this project more to be convinced, but I trust the implementation and algorithm choice in core R way more than any other stats package except possibly SAS: among other reasons it has far more of the right eyeballs looking at the code. Picking numerically reliable implementations of most estimators is not trivial without the right training. Now, I don't know how much needed to be rewritten for this project, so that's just my general opinion.
Its easy to get addicted to R syntax / capabilities. (Read: Data scientists are lazy)