I love R and I love programming in it, but I have always thought I need to learn Julia due to a few things including speed, but that the R community keeps coming out with great answers to those questions where Julia keeps my interest. I don't see how this would speed up my typical R programming or code to be worth learning Haskell. What am I missing and yes I read the whole article.<p>I have found Haskell very difficult to use with Cabal and its package management. The reason I went to Haskell was to teach myself functional programming. After struggling and going through 2 books I still felt like I hated Haskell due to making the environment just work. I work in three different locations and to get all 5 computers to work in Haskell was a serious pain. This lead me to see what else is out there. It lead me to <a href="https://www.coursera.org/course/proglang" rel="nofollow">https://www.coursera.org/course/proglang</a> which introduced me to Racket and I loved it and felt that Racket was the perfect fit for me.
Looks fun. However, what is REALLY slow in R isn't the interpreter or garbage collector: but some of the object re-allocation patterns you accidentally trigger. Here is my note making some comparisons and recommendations on writing fast code in R: <a href="http://www.win-vector.com/blog/2015/07/efficient-accumulation-in-r/" rel="nofollow">http://www.win-vector.com/blog/2015/07/efficient-accumulatio...</a>
Well haskell is not the only option.<p>From .NET: <a href="http://rdotnet.codeplex.com/" rel="nofollow">http://rdotnet.codeplex.com/</a>
there is also a dataprovider directly to F# : <a href="http://bluemountaincapital.github.io/FSharpRProvider/" rel="nofollow">http://bluemountaincapital.github.io/FSharpRProvider/</a><p>Also there is C++ binding available also: <a href="http://www.rcpp.org/" rel="nofollow">http://www.rcpp.org/</a>
How does garbage collection work? Does this version improve on the R I know from a year ago, which had a reference counting system with only three values: 0, 1, and 2+?
While this really has nothing to do with programming R, this is a neat way to use Haskell for some statistics/data science tasks whilst making use of all the work that has gone into R over the years.<p>I personally don't see this as a way of using R, rather a way of using Haskell.
I don't know almost anything about Haskell (tried to learn it some years ago but never pass form the basics).<p>Yet from what I'm seeing we are only calling R functions from Haskell. I'm probably missing something on the explanation, but how does this speed up R?