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The Net Takeaway: J vs. R


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J vs. R · 09/13/2007 11:15 PM, Analysis

When we think of “statistical” programming languages, most of us in the stats field think of S and its open source cousin, R. I have a ton of content and information on R, reachable from the menu in the right hand side labeled R Statistical System. And so, having worked with SPSS, SAS, Stata, and R/S, I thought I had seen it all.

But I was surprised to see mention of a clustering algorithm implemented in “J601”. Some searching revealed that J is the next generation of Ken Iverson’s “APL” programming language. APL was known as the programming language with all the strange characters: comp sci people loved it, and everyone thought it was a nightmare. See some samples at the Wikipedia page on APL.

So, J appears to be a combination of the terse syntax of APL with a “functional programming” approach. Like R, it has a large collection of built in statistical and analytic functions optimized for matrices of data, and is appears to be used mostly by quantitative trading analyzers. While most of the stats/data miners I know in the marketing field tend towards the languages I mentioned earlier, its always good to know about the ways people solve problems in other fields.

See more about “J” at its home page, After looking it over, I think R is much easier to understand, but who knows? This could be the language you’ve been looking for…

BTW, if you are interested, another popular quantitative trading analysis language also derived from APL is K, which is part of the Kx column-oriented database system (which merges in-memory with disk in some impressive ways). See more at Wikipedia’s K page and it’s home at Kx Systems.

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