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I like R, and I think it has some great DSLs. Plus a wealth of packages implementing many methods not found elsewhere. I also like its Scheme roots. But I think

by nextos 8y ago

I like R, and I think it has some great DSLs. Plus a wealth of packages implementing many methods not found elsewhere. I also like its Scheme roots. But I think R's design is starting to show its limitations. Ross Ihaka, one of the main developers published some papers pointing to these issues and suggesting to start over using another Lisp-based language [1]. I don't think he has developed anything yet, but interestingly Julia is quite Lisp-based and addresses many of the problems he mentioned. I've used R heavily for many years, but I'm toying with the idea of transitioning to Julia because the combination of multiple dispatch and a type system designed for efficient code is extremely pleasant to use. It's a simpler and faster language, plus I can keep calling R code when needed. There are also awesome packages that are getting developed in Julia and not found elsewhere [2]. [1] https://www.stat.auckland.ac.nz/%7Eihaka/downloads/JSM-2010.pdf https://www.stat.auckland.ac.nz/%7Eihaka/downloads/JSM-2010.... [2] https://discourse.julialang.org/t/what-package-s-are-state-of-the-art-or-attract-you-to-julia-and-make-you-stay-there-not-easily-replicateable-in-e-g-python-r-matlab/11294 https://discourse.julialang.org/t/what-package-s-are-state-o...

peatmoss 8y ago
Racket (see my other comment) is my dream for the right place to start over for data and stats, but Julia is a pretty reasonable consolation prize. I feel like there was enormous excitement about Julia early on, but that I rarely hear much about Julia in the stats space these days. Several years ago now, I took an introductory Bayesian stats course as part of a PhD program. At the time, I was impressed that I was able to do the obnoxious toy problems (the almost always unrealistic conjugate prior based examples) because the distributions(?) package had built-in knowledge of conjugacy. I think a lot of people are waiting for a "go signal" before jumping into Julia. I think at some point, if R Studio were to announce support for Julia within the R Studio IDE, I suspect that would serve as the signal. As for me, Julia has been well supported by Emacs Speaks Statistics forever, so I feel like I'm already living in the future of Julia editor tooling. Maybe it's time for me to give Julia another look.
- nextos 8y ago
  I think we are already seeing the first group of power users migrating to Julia. Those that are unhappy with the current status quo and look for a better language to create new stuff. In my opinion, a sign of this are new packages that are quite unique to Julia: JuMP, DifferentialEquations, OnlineStats...

by nextos 8y ago

peatmoss 8y ago

Racket (see my other comment) is my dream for the right place to start over for data and stats, but Julia is a pretty reasonable consolation prize. I feel like there was enormous excitement about Julia early on, but that I rarely hear much about Julia in the stats space these days. Several years ago now, I took an introductory Bayesian stats course as part of a PhD program. At the time, I was impressed that I was able to do the obnoxious toy problems (the almost always unrealistic conjugate prior based examples) because the distributions(?) package had built-in knowledge of conjugacy. I think a lot of people are waiting for a "go signal" before jumping into Julia. I think at some point, if R Studio were to announce support for Julia within the R Studio IDE, I suspect that would serve as the signal. As for me, Julia has been well supported by Emacs Speaks Statistics forever, so I feel like I'm already living in the future of Julia editor tooling. Maybe it's time for me to give Julia another look.

nextos 8y ago
I think we are already seeing the first group of power users migrating to Julia. Those that are unhappy with the current status quo and look for a better language to create new stuff. In my opinion, a sign of this are new packages that are quite unique to Julia: JuMP, DifferentialEquations, OnlineStats...