Wednesday, 23 November 2011

Calling NAG routines from R

R is a widely-used environment for statistical computing and data analysis. It is one of the modern implementations of the S programming language (i.e. much code written in S will run unaltered in R) although its underlying semantics are derived from Scheme. R is Free Software.

The capabilities of R can be extended through the use of add-on packages and a large number of these are available from the Comprehensive R Archive Network (CRAN). Some users have expressed an interest in calling NAG Library routines from within R; accordingly, we have recently created a package which provides access to some of NAG's numerical functionality. More specifically, the NAGFWrappers R package contains the local and global optimization chapters of the NAG Fortran Library, together with a few nearest correlation matrix solvers and some other simpler routines. The package incorporates documentation in the so-called Rdoc style that will automatically produce help pages within the R system (see figure below), and also in HTML and PDF - for example, here is the full list of NAG routines that are contained in the package.

For completeness, and to help R users further, we have also published more general instructions about how to use the R extension mechanisms to access any NAG routine from within R.

The original version of NAGFWrappers has been available since mid-2011; we have just updated it to use Mark 23 of the Fortran Library, and are releasing R binary packages for Windows 32 bit and Windows 64 bit, along with the R source package which can be used on other platforms (for example, we have built and run it on 64 bit Linux).

It should perhaps be noted that this is a preview release of the package, which is aimed at obtaining user feedback. Although it has been built and run on the platforms mentioned above, it is not a NAG product. We are keen to receive user feedback, and will respond to technical queries and problem reports via so that we can further refine this package and make it still more useful to the R community.

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