Abstract
R [38] is a powerful and flexible environment for research computing. Written by Ross Ihaka, Robert Gentleman (hence the name “R”), the R Core Development Team, and an army of volunteers, R provides a wider range of analytical and graphical commands than any other software. The fact that this level of power is available free of charge has dramatically changed the landscape of research software.
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Notes
- 1.
For a fascinating history of S and R, see Appendix A of Software for Data Analysis: Programming with R [5].
References
John M. Chambers. Software for Data Analysis: Programming with R. Springer, 2008.
The R Foundation for Statistical Computing. R: Regulatory compliance and validation issues a guidance document for the use of r in regulated clinical trial environments, 2008. Available from http://www.r-project.org/doc/R-FDA.pdf.
Roger B. Newson. Rsource: Stata module to run r from inside stata using an r source file, 2008. Available from http://ideas.repec.org/c/boc/bocode/s456847.html.
R Development Core Team. R: A Language and Environment for Statistical Computing. Available from http://www.R-project.org, 2008.
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Muenchen, R.A., Hilbe, J.M. (2010). Introduction. In: R for Stata Users. Statistics and Computing. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1318-0_1
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