Using The R Project for Statistical Computing

Introduction

I have been looking into the feasibility of using the R statistical package for adding better statisitcal models and analysis for our software . R is extremely powerful. Almost any statistical method is represented in it.  The question I had is: How do I use R as a backend tool for our report generating software written primarily in VB.Net, SQL, and HTML?

Resulting Research

What I found out was that R plays nice with just about any technology available. There are tools for using R with a variety of interfaces written in on other languages  where you can go back and forth from and to R:

Dot Net - http://www.u.arizona.edu/~ryckman/RNet.php

Python - http://rpy.sourceforge.net/ and http://www.omegahat.org/RSPython/

Excel  - http://www.ci.tuwien.ac.at/Conferences/useR-2004/abstracts/Baier+Neuwirth.pdf

In my search,  I found that in order to truly embed R’s functionality and features in a windows application using Microsoft’s DCOM technology will get me the farthest  fastest.  It gives us as cloase to an API for R as possible

C# Example - http://www.codeproject.com/KB/cs/RtoCSharp.aspx

VB.Net Example - http://mailman.csd.univie.ac.at/pipermail/rcom-l/2004-September/000358.html

A  guide to importing and exporting data to and from R. - http://cran.r-project.org/doc/manuals/R-data.html

How to import Excel data into a statistical application package, the easy way - http://lane.stanford.edu/howto/index.html?id=3672

Import Excel .xls files into R - http://www.lamnk.com/blog/econometrics/import-excel-xls-files-into-r/