Open Source Software

R - Open Source Statistical Software

While working on my praxis during my Doctor of Engineering program, I tried to do a multiple linear regression in Excel--and discovered Excel's limitations. Since I didn't have budget money for SAS and couldn't move the data to the university's computers for confidentiality reasons. I started frantically surfing the web: "open source" "free" "statistics" "linear" "regression".

I downloaded several programs, most of which had even more problems than Excel. I finally downloaded a program called "R" and was able to install it, load my data, and run my regression in less than an hour. Although the language was very different from all of the languages that I knew (or for that matter know), it worked reliably, and did what I needed.

More than 12 years later, I am still an R user and have attended the UseR! conferences in Ames (2007), Dortmund (2008), Rennes (2009), Coventry (2011) and Albacete (2013). The links that follow provide a few resources for this great statistical package. R is now used in a number of Fortune 500 firms, including Google (which does its own internal distribution) and a number of pharmaceutical companies.

  • R project web site Provides links to mirrors for downloading.
  • Revolution Analytics is a commercial vendor that distributes a supported version of R and it's related packages. The Revolution Analytics interpreter has some proprietary features that are of use for parallel computing and large datasets.
  • RStudio offers a wonderful free integrated development environment for R, and various educational offerings. Hadley Wickham is one of the most prolific and respected package writers.
  • RMetrics is a project to develop R packages for the financial engineering. This user group has its own conference, and most of the finance crowd goes to this conference rather than the general UseR! conference.
  • RGeo is a project to develop geospatial analysis packages for R.
  • BioConductor is a very large project to develop software for genomic and pharmalogical research. Pharmaceutical firms were among the first to adopt R.

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