This project will has moved to the address https://rclr.codeplex.com. As of December 2014, newer packages are at the new siteProject DescriptionAccessing the Common Language Runtime (.NET or Mono) from the R statistical software, in-process.
Keywordsinterfacing R and .NET; R and Mono; R to .NET; CLR hosting; embedding Mono
Installation instructionsPlease follow the
Installing R packages in the
Documentation. A
Quick start page documents the first steps to get the library loaded in R.
News2014-12-18: Release 0.7-2 is available from
https://rclr.codeplex.com.
2013-09-21: Release 0.5-2 (beta 5)
- Fixed memory leaks when passing R vectors to .NET
- Major improvement to the handling and reporting of CLR exceptions on MS.NET
- The download page also has a tarball of the sources
- Support for Mono included in the windows binaries. Date-time handling is the main lagging feature.
SummaryThe
R Project for Statistical Computing has seen an outstanding adoption in many scientific fields and is a tool of choice for many. Some things are still better done in other languages (C, Fortran, Java, .NET, etc.).
There are ways to link R in-process with most languages, however the interoperability with .NET is lagging.
R.NET offers one way to access R from a Common Language Runtime implementation (CLR).
The project rClr offers the access to a CLR from R in a manner natural to R users.
To give a feel for the capabilities, below is an extract from the tutorials. A hydrology model written in C# and its time series outputs are visualized in R.

rClr aims to be for .NET CLR implementations (.NET framework and Mono) what
rJava is for Java.