Abstract
A language for data analysis and graphics. This definition of R was used by Ross Ihaka and Robert Gentleman in the title of their 1996 paper (Ihaka and Gentleman 1996) outlining their experience of designing and implementing the R software. It’s safe to say this remains the essence of what R is; however, it’s tough to encapsulate such a diverse programming language into a single phrase.
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Notes
- 1.
Consequently, R is named partly after its authors (Ross and Robert) and partly as a play on the name of S.
- 2.
See Roger Peng’s R programming for Data Science for further, yet concise, details on S and R’s history.
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- 4.
Open-source is far from new as it has been around for decades (i.e. A-2 in the 1950s, IBM’s ACP in the ’60s, Tiny BASIC in the ’70s) but has gained prominence since the late 1990s.
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- 7.
See The Journal of Statistical Software and The R Journal.
- 8.
Bibliography
Ihaka, Ross, and Robert Gentleman. “R: A language for data analysis and graphics.” Journal of Computational and Graphical Statistics 5, no. 3 (1996):299–314.
Morandat, Floréal, Brandon Hill, Leo Osvald, and Jan Vitek. “Evaluating the design of the R language.” In European Conference on Object-Oriented Programming, pp. 104–131. Springer Berlin Heidelberg, 2012.
Pollack, R. D., Klimberg, R. K., and Boklage, S.H. “The true cost of ‘free’ statistical software.” OR/MS Today, vol. 42, no. 5 (2015):34–35.
Boehmke, Bradley C. and Jackson, Ross A. “Unpacking the true cost of ‘free’ statistical software.” OR/MS Today, vol. 43, no. 1 (2016):26–27.
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Boehmke, B.C. (2016). Introduction to R. In: Data Wrangling with R. Use R!. Springer, Cham. https://doi.org/10.1007/978-3-319-45599-0_2
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DOI: https://doi.org/10.1007/978-3-319-45599-0_2
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