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R.NET enables .NET Framework to collaborate with R statistical computing. R.NET requires .NET Framework 4 and native DLLs installed with R environment. You need no other extra installations. Enjoy statistics and programming in your special language with R.

http://rdotnet.codeplex.com/Tags | interop r statistics |

Implementation | CSharp |

License | BSD |

Platform | Windows |

Clar is a minimal C unit testing framework. It's been written to replace theold framework in [libgit2][libgit2], but it's both very versatile andstraightforward to use.Can you count to funk?- **Zero: Initialize test directory** ~~~~ sh $ mkdir tests $ cp -r $CLAR_ROOT/clar* tests $ cp $CLAR_ROOT/test/clar_test.h tests $ cp $CLAR_ROOT/test/main.c.sample tests/main.c ~~~~- **One: Write some tests** File: tests/adding.c: ~~~~ c /* adding.c for the "Adding" suite */

Scripts to be used with the R Statistics software

Code for analysing MILC propagators using the R statistics package.

R interface to Nike+ API and basic statistics/visualization

Stock trading simulation + buy/sell predictor for R statistics suite

A package to produce statistics based on the source code of other R packages.

Exercises from Verzani's simpleR - Using R for Introductory Statistics

an exercise from Using R for Introductory Statistics by John Verzani

IPSUR, Introduction to Probability and Statistics Using R, is a textbook written for an undergraduate course in probability and statistics. IPSUR is FREE, in the GNU sense of the word.

Slides and code on spatial statistics in R.

Statistics for MINC volumes: A library to integrate voxel-based statistics for MINC volumes into the R environment. Supports getting and writing of MINC volumes, running voxel-wise linear models, correlations, etc.; correcting for multiple comparisons using the False Discovery Rate, and more. With contributions from Jason Lerch, Jim Nikelski and Matthijs van Eede. Some additional information can be found here: