Thursday, September 9, 2010

Changing statistical languages

Even when a current programming language has drawbacks, it can be hard to change to a more optimal language due to the investment in the current language. Here is a comment from Julien Cornebise:


But R is here and in everyday use, and the matter is more of making it worth using, to its full potential. I have no special attachment to R, but any breakthrough language that would not be entirely compatible with the massive library contributed over the years would be doomed to fail to pick-up the everyday statistician—and we’re talking here about far-fetched long-term moves. Sanitary breakthrough, but harder to make happen when such an anchor is here.


R is a pretty amazing language and, as a long term SAS user, I must admit that I am delighted by the graphics and the cool packages. Of course, the dark side of such a rich library is needing to learn about the reliability and limitations of all of the different packages.

H/t: Andrew Gelman

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