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Comment by gruseom | Hacker News Reader

Meanwhile the creator of R wants to return to a Lisp-based statistics environment:

http://books.google.com/books?id=8Cf16JkKz30C&pg=PA21...

Another interesting paper hidden behind the academic firewall.

At least in the physics world people just post everything to arXiv and their personal websites. This way you only need to pay attention to a couple of places to keep up to date.

As I said in another thread, most computer science papers are on authors' webpages. Then this one comes along - but it looks like the authors are stat people. I don't know what their culture is - and what kind of copyright agreements they sign.

I can access the paper because my school subscribes. If anyone wants to read it, figure out how to email me and I'll send a copy.

While searching, I did find a brief email from Ihaka talking about the jump to Lisp: https://stat.ethz.ch/pipermail/r-devel/2008-May/049501.html

Thanks :-)

Even in certain areas of computer science (specifically, machine learning) nearly all recent articles are open. I find in most cases that both statisticians and computer scientists tend to post links to pdfs or ps on their websites as well.

Statistics and Lisp have a long, long history together. Before R took off, many academic statisticians were using Lisp-Stat, Luke Tierney's tool from UMN. Luke has now been spending time helping R, and it shows in how it is starting to adopt more of a Lisp mentality. The referenced paper also shows the Lisp background from R (and S) history. R syntax can be confusing enough; Lisp really has a learning effort such that most analysts just don't have the time to invest in it unless they were trained in it early on.

Maxima (http://maxima.sourceforge.net/) is a nice CAS, sort of similar to Maple, IIRC. It is written in Lisp but hides that from the interface layer.

Lush is a LISP-style environment for scientific computing:

http://lush.sourceforge.net/

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