Your verification ID is: guDlT7MCuIOFFHSbB3jPFN5QLaQ Big Computing: R 2.14 is release and R 2.15 is now a year away.....

Tuesday, November 1, 2011

R 2.14 is release and R 2.15 is now a year away.....

I missed this yesterday because I was out trick or treating, but R 2.14 was released. I love that on CRAN it is called R 2.14.0 ( Great Pumpkin). Here is the link to download it now.

David Smith did a nice summary of what 2.14.0 on his Revolutions Blog which I have copied here:


As scheduled, the first release of the new R 2.14 series is now available for download in source code form. As of this writing, pre-compiled binaries for Windows, Linux and MacOS aren't yet available, but will appear on your local CRAN mirror in the next couple of days.
One of the biggest changes in 2.14 is the introduction of the new "parallel" package as a standard part of R. As the NEWS file explains:
[The parallel package] incorporates (slightly revised) copies of packages multicore and snow (excluding MPI, PVM and NWS clusters).  Code written to use the higher-level API functions in those packages should work unchanged (apart from changing any references to their namespaces to a reference to parallel, and links explicitly to multicore or snow on help pages).
In addition, all of the standard (base and recommended) R packages are now byte-compiled on installation, which improves R's performance in several situations.
Other improvements include better alignment of math and text in graphics, Rao's efficient score test for GLM's, the ability to draw curves from functions with plot.function, a new L'Ecuyer random number generator, improved access to documentation (especially vignettes), and several minor bug-fixes.
With R now on an annual (rather than six-monthly) update cycle, R 2.15 is not expected until October 2012 (with point releases for the 2.14.x series likely in the interim).

Thanks David.

2.14.0 continues the trend to incorporate performance enhancements into base R. Parallel packages have long existed for R, but this addition to base R is a nice touch as is the byte-compiling. I believe the changing to an annual release schedule is also a great idea that will work better with the commercial customers than the current system of six month cycles. Most of the commercial R users that I have dealt with update on an annual basis and would choose to update on the odd or even numbered revisions. This meshing of the updates will help those commercial users out a great deal.

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