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R (programming language)

From Wikipedia, the free encyclopedia
This article is about the programming language. For the eighteenth letter of the English alphabet, see R. For other uses, see R (disambiguation).

R
R terminal
ParadigmsMulti-paradigm: procedural, object-oriented, functional, reflective, imperative, array[1]
Designed byRoss Ihaka and Robert Gentleman
DeveloperR Core Team
First appearedAugust 1993; 31 years ago (1993-08)
Stable release
4.5.0[2] Edit this on Wikidata / 11 April 2025; 15 days ago (11 April 2025)
Typing disciplineDynamic
Platformarm64 and x86-64
LicenseGPL-2.0-or-later[3]
Filename extensions
  • .r[4]
  • .rdata
  • .rhistory
  • .rds
  • .rda[5]
Websiter-project.org
Influenced by
Influenced
Julia[7]pandas[8]

R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis.[9]

The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data.

R software is open-source and free software. R is licensed by the GNU Project and available under the GNU General Public License.[3] It's written primarily in C, Fortran, and R itself. Precompiledexecutables are provided for various operating systems.

As an interpreted language, R has a native command line interface. Moreover, multiple third-partygraphical user interfaces are available, such as RStudio—an integrated development environment—and Jupyter—a notebook interface.

History

[edit]
Ross Ihaka, co-originator of R
Robert Gentleman, co-originator of R

R was started by professors Ross Ihaka and Robert Gentleman as a programming language to teach introductory statistics at the University of Auckland.[10] The language was inspired by the S programming language, with most S programs able to run unaltered in R.[6] The language was also inspired by Scheme'slexical scoping, allowing for local variables.[1]

The name of the language, R, comes from being both an S language successor as well as the shared first letter of the authors, Ross and Robert.[11] In August 1993, Ihaka and Gentleman posted a binary of R on StatLib — a data archive website.[12] At the same time, they announced the posting on the s-newsmailing list.[13] On 5 December 1997, R became a GNU project when version 0.60 was released.[14] On 29 February 2000, the 1.0 version was released.[15]

Packages

[edit]
Main article: R package
refer to caption
Violin plot created from the R visualization package ggplot2

R packages are collections of functions, documentation, and data that expand R.[16] For example, packages add report features such as RMarkdown, Quarto,[17]knitr and Sweave. Packages also add the capability to implement various statistical techniques such as linear, generalized linear and nonlinear modeling, classical statistical tests, spatial analysis, time-series analysis, and clustering. Easy package installation and use have contributed to the language's adoption in data science.[18]

Base packages are immediately available when starting R and provide the necessary syntax and commands for programming, computing, graphics production, basic arithmetic, and statistical functionality.[19]

The Comprehensive R Archive Network (CRAN) was founded in 1997 by Kurt Hornik and Friedrich Leisch to host R's source code, executable files, documentation, and user-created packages.[20] Its name and scope mimic the Comprehensive TeX Archive Network and the Comprehensive Perl Archive Network.[20] CRAN originally had three mirrors and 12 contributed packages.[21] As of 16 October 2024, it has 99 mirrors[22] and 21,513 contributed packages.[23] Packages are also available on repositories R-Forge, Omegahat, and GitHub.[24][25][26]

The Task Views on the CRAN web site list packages in fields such as causal inference, finance, genetics, high-performance computing, machine learning, medical imaging, meta-analysis, social sciences, and spatial statistics.

The Bioconductor project provides packages for genomic data analysis, complementary DNA, microarray, and high-throughput sequencing methods.

The tidyverse package bundles several subsidiary packages that provide a common interface for tasks related to accessing and processing "tidy data",[27] data contained in a two-dimensional table with a single row for each observation and a single column for each variable.[28]

Installing a package occurs only once. For example, to install the tidyverse package:[28]

> install.packages("tidyverse")

To load the functions, data, and documentation of a package, one executes the library() function. To load tidyverse:[a]

> # Package name can be enclosed in quotes> library("tidyverse")> # But also the package name can be called without quotes> library(tidyverse)

Interfaces

[edit]

R comes installed with a command line console. Available for installation are various integrated development environments (IDE). IDEs for R include R.app[29] (OSX/macOS only), Rattle GUI, R Commander, RKWard, RStudio, and Tinn-R.[30]

General purpose IDEs that support R include Eclipse via the StatET plugin and Visual Studio via R Tools for Visual Studio.

Editors that support R include Emacs, Vim via the Nvim-R plugin, Kate, LyX via Sweave, WinEdt (website), and Jupyter (website).

Scripting languages that support R include Python (website), Perl (website), Ruby (source code), F# (website), and Julia (source code).

General purpose programming languages that support R include Java via the Rserve socket server, and .NET C# (website).

Statistical frameworks which use R in the background include Jamovi and JASP.[citation needed]

Community

[edit]

The R Core Team was founded in 1997 to maintain the Rsource code. The R Foundation for Statistical Computing was founded in April 2003 to provide financial support. The R Consortium is a Linux Foundation project to develop R infrastructure.

The R Journal is an open access, academic journal which features short to medium-length articles on the use and development of R. It includes articles on packages, programming tips, CRAN news, and foundation news.

The R community hosts many conferences and in-person meetups - see the community maintained GitHub list. These groups include:

Implementations

[edit]

The main R implementation is written primarily in C, Fortran, and R itself. Other implementations include:

Microsoft R Open (MRO) was an R implementation. As of 30 June 2021, Microsoft started to phase out MRO in favor of the CRAN distribution.[33]

Commercial support

[edit]

Although R is an open-source project, some companies provide commercial support:

  • Oracle provides commercial support for the Big Data Appliance, which integrates R into its other products.
  • IBM provides commercial support for in-Hadoop execution of R.

Examples

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Hello, World!

[edit]

"Hello, World!" program: 

> print("Hello, World!")[1] "Hello, World!"

Basic syntax

[edit]

The following examples illustrate the basic syntax of the language and use of the command-line interface. (An expanded list of standard language features can be found in the R manual, "An Introduction to R".[34])

In R, the generally preferred assignment operator is an arrow made from two characters <-, although = can be used in some cases.[35]

> x<-1:6# Create a numeric vector in the current environment> y<-x^2# Create vector based on the values in x.> print(y)# Print the vector’s contents.[1] 1 4 9 16 25 36> z<-x+y# Create a new vector that is the sum of x and y> z# Return the contents of z to the current environment.[1] 2 6 12 20 30 42> z_matrix<-matrix(z,nrow=3)# Create a new matrix that turns the vector z into a 3x2 matrix object> z_matrix [,1] [,2][1,] 2 20[2,] 6 30[3,] 12 42> 2*t(z_matrix)-2# Transpose the matrix, multiply every element by 2, subtract 2 from each element in the matrix, and return the results to the terminal. [,1] [,2] [,3][1,] 2 10 22[2,] 38 58 82> new_df<-data.frame(t(z_matrix),row.names=c("A","B"))# Create a new data.frame object that contains the data from a transposed z_matrix, with row names 'A' and 'B'> names(new_df)<-c("X","Y","Z")# Set the column names of new_df as X, Y, and Z.> print(new_df)# Print the current results. X Y ZA 2 6 12B 20 30 42> new_df$Z# Output the Z column[1] 12 42> new_df$Z==new_df['Z']&&new_df[3]==new_df$Z# The data.frame column Z can be accessed using $Z, ['Z'], or [3] syntax and the values are the same. [1] TRUE> attributes(new_df)# Print attributes information about the new_df object$names[1] "X" "Y" "Z"$row.names[1] "A" "B"$class[1] "data.frame"> attributes(new_df)$row.names<-c("one","two")# Access and then change the row.names attribute; can also be done using rownames()> new_df X Y Zone 2 6 12two 20 30 42

Structure of a function

[edit]

One of R's strengths is the ease of creating new functions.[36]Objects in the function body remain local to the function, and any data type may be returned. In R, almost all functions and all user-defined functions are closures.[37]

Create a function: 

# The input parameters are x and y.# The function returns a linear combination of x and y.f<-function(x,y){z<-3*x+4*y# An explicit return() statement is optional, could be replaced with simply `z`.return(z)}# Alternatively, the last statement executed is implicitly returned.f<-function(x,y)3*x+4*y

Usage output: 

> f(1,2)[1] 11> f(c(1,2,3),c(5,3,4))[1] 23 18 25> f(1:3,4)[1] 19 22 25

It is possible to define functions to be used as infix operators with the special syntax `%name%` where "name" is the function variable name: 

> `%sumx2y2%`<-function(e1,e2){e1^2+e2^2}> 1:3%sumx2y2%-(1:3)[1] 2 8 18

Since version 4.1.0 functions can be written in a short notation, which is useful for passing anonymous functions to higher-order functions:[38]

> sapply(1:5,\(i)i^2)# here \(i) is the same as function(i) [1] 1 4 9 16 25

Native pipe operator

[edit]

In R version 4.1.0, a native pipe operator, |>, was introduced.[39] This operator allows users to chain functions together one after another, instead of a nested function call. 

> nrow(subset(mtcars,cyl==4))# Nested without the pipe character[1] 11> mtcars|>subset(cyl==4)|>nrow()# Using the pipe character[1] 11

Another alternative to nested functions, in contrast to using the pipe character, is using intermediate objects: 

> mtcars_subset_rows<-subset(mtcars,cyl==4)> num_mtcars_subset<-nrow(mtcars_subset_rows)> print(num_mtcars_subset)[1] 11

While the pipe operator can produce code that is easier to read, it has been advised to pipe together at most 10 to 15 lines and chunk code into sub-tasks which are saved into objects with meaningful names.[40] Here is an example with fewer than 10 lines that some readers may still struggle to grasp without intermediate named steps:

(\(x,n=42,key=c(letters,LETTERS," ",":",")"))strsplit(x,"")[[1]]|>(Vectorize(\(chr)which(chr==key)-1))()|>(`+`)(n)|>(`%%`)(length(key))|>(\(i)key[i+1])()|>paste(collapse=""))("duvFkvFksnvEyLkHAErnqnoyr")

Object-oriented programming

[edit]

The R language has native support for object-oriented programming. There are two native frameworks, the so-called S3 and S4 systems. The former, being more informal, supports single dispatch on the first argument and objects are assigned to a class by just setting a "class" attribute in each object. The latter is a Common Lisp Object System (CLOS)-like system of formal classes (also derived from S) and generic methods that supports multiple dispatch and multiple inheritance[41]

In the example, summary is a generic function that dispatches to different methods depending on whether its argument is a numeric vector or a "factor": 

> data<-c("a","b","c","a",NA)> summary(data) Length Class Mode  5 character character > summary(as.factor(data)) a b c NA's  2 1 1 1

Modeling and plotting

[edit]
Diagnostic plots from plotting "model" (q.v. "plot.lm()" function). Notice the mathematical notation allowed in labels (lower left plot).

The R language has built-in support for data modeling and graphics. The following example shows how R can generate and plot a linear model with residuals. 

# Create x and y valuesx<-1:6y<-x^2# Linear regression model y = A + B * xmodel<-lm(y~x)# Display an in-depth summary of the modelsummary(model)# Create a 2 by 2 layout for figurespar(mfrow=c(2,2))# Output diagnostic plots of the modelplot(model)

Output: 

Residuals: 1 2 3 4 5 6 7 8 9 10 3.3333 -0.6667 -2.6667 -2.6667 -0.6667 3.3333Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -9.3333 2.8441 -3.282 0.030453 * x 7.0000 0.7303 9.585 0.000662 ***---Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1Residual standard error: 3.055 on 4 degrees of freedomMultiple R-squared: 0.9583, Adjusted R-squared: 0.9478F-statistic: 91.88 on 1 and 4 DF, p-value: 0.000662

Mandelbrot set

[edit]
"Mandelbrot.gif" graphic created in R. (Note: Colors differ from actual output.)

This Mandelbrot set example highlights the use of complex numbers. It models the first 20 iterations of the equationz = z2 + c, where c represents different complex constants.

Install the package that provides the write.gif() function beforehand: 

install.packages("caTools")

R Source code: 

library(caTools)jet.colors<-colorRampPalette(c("green","pink","#007FFF","cyan","#7FFF7F","white","#FF7F00","red","#7F0000"))dx<-1500# define widthdy<-1400# define heightC<-complex(real=rep(seq(-2.2,1.0,length.out=dx),each=dy),imag=rep(seq(-1.2,1.2,length.out=dy),times=dx))# reshape as matrix of complex numbersC<-matrix(C,dy,dx)# initialize output 3D arrayX<-array(0,c(dy,dx,20))Z<-0# loop with 20 iterationsfor (kin1:20){# the central difference equationZ<-Z^2+C# capture the resultsX[,,k]<-exp(-abs(Z))}write.gif(X,"Mandelbrot.gif",col=jet.colors,delay=100)

Version names

[edit]
A CD with autographs on it
CD of R Version 1.0.0, autographed by the core team of R, photographed R in Quebec City in 2019

All R version releases from 2.14.0 onward have codenames that make reference to Peanuts comics and films.[42][43][44]

In 2018, core R developer Peter Dalgaard presented a history of R releases since 1997.[45] Some notable early releases before the named releases include:

  • Version 1.0.0 released on 29 February 2000 (2000-02-29), a leap day
  • Version 2.0.0 released on 4 October 2004 (2004-10-04), "which at least had a nice ring to it"[45]

The idea of naming R version releases was inspired by the Debian and Ubuntu version naming system. Dalgaard also noted that another reason for the use of Peanuts references for R codenames is because, "everyone in statistics is a P-nut".[45]

R release codenames
Version Release date Name Peanuts reference Reference
4.5.0 2025-04-11 How About a Twenty-Six [46][47]
4.4.3 2025-02-28 Trophy Case [48][49]
4.4.2 2024-10-31 Pile of Leaves [50][51]
4.4.1 2024-06-14 Race for Your Life [52][53]
4.4.0 2024-04-24 Puppy Cup [54][55]
4.3.3 2024-02-29 Angel Food Cake [56][57]
4.3.2 2023-10-31 Eye Holes [58][59]
4.3.1 2023-06-16 Beagle Scouts [60][61]
4.3.0 2023-04-21 Already Tomorrow [62][63][64][65]
4.2.3 2023-03-15 Shortstop Beagle [66][67]
4.2.2 2022-10-31 Innocent and Trusting [68][69]
4.2.1 2022-06-23 Funny-Looking Kid [70][71][72][73][74][75][76]
4.2.0 2022-04-22 Vigorous Calisthenics [77][78]
4.1.3 2022-03-10 One Push-Up [77][79]
4.1.2 2021-11-01 Bird Hippie [80][81][79]
4.1.1 2021-08-10 Kick Things [82][83]
4.1.0 2021-05-18 Camp Pontanezen [84][85]
4.0.5 2021-03-31 Shake and Throw [86][87]
4.0.4 2021-02-15 Lost Library Book [88][89][90][91]
4.0.3 2020-10-10 Bunny-Wunnies Freak Out [92][93]
4.0.2 2020-06-22 Taking Off Again [94][95]
4.0.1 2020-06-06 See Things Now [96][97]
4.0.0 2020-04-24 Arbor Day [98][99]
3.6.3 2020-02-29 Holding the Windsock [100][101]
3.6.2 2019-12-12 Dark and Stormy Night See It was a dark and stormy night#Literature[102][103]
3.6.1 2019-07-05 Action of the Toes [104][105]
3.6.0 2019-04-26 Planting of a Tree [106][107]
3.5.3 2019-03-11 Great Truth [108][109]
3.5.2 2018-12-20 Eggshell Igloos [110][111]
3.5.1 2018-07-02 Feather Spray [112][113]
3.5.0 2018-04-23 Joy in Playing [114][115]
3.4.4 2018-03-15 Someone to Lean On [116][117][118][119]
3.4.3 2017-11-30 Kite-Eating Tree See Kite-Eating Tree[120][121]
3.4.2 2017-09-28 Short Summer See It Was a Short Summer, Charlie Brown[122]
3.4.1 2017-06-30 Single Candle [123][124]
3.4.0 2017-04-21 You Stupid Darkness [123][125]
3.3.3 2017-03-06 Another Canoe [126][127]
3.3.2 2016-10-31 Sincere Pumpkin Patch [128][129]
3.3.1 2016-06-21 Bug in Your Hair [130][131]
3.3.0 2016-05-03 Supposedly Educational [132][133]
3.2.5 2016-04-11 Very, Very Secure Dishes [134][135][136][137]
3.2.4 2016-03-11 Very Secure Dishes [134][138]
3.2.3 2015-12-10 Wooden Christmas-Tree See A Charlie Brown Christmas[139][140]
3.2.2 2015-08-14 Fire Safety [141][142][143]
3.2.1 2015-06-18 World-Famous Astronaut [144][145]
3.2.0 2015-04-16 Full of Ingredients [146][147]
3.1.3 2015-03-09 Smooth Sidewalk [148][page needed][149]
3.1.2 2014-10-31 Pumpkin Helmet See You're a Good Sport, Charlie Brown[150]
3.1.1 2014-07-10 Sock it to Me [151][152][153][154][155]
3.1.0 2014-04-10 Spring Dance [104][156]
3.0.3 2014-03-06 Warm Puppy [157][158]
3.0.2 2013-09-25 Frisbee Sailing [159][160]
3.0.1 2013-05-16 Good Sport [161][162]
3.0.0 2013-04-03 Masked Marvel [163][164]
2.15.3 2013-03-01 Security Blanket [165][166]
2.15.2 2012-10-26 Trick or Treat [167][168]
2.15.1 2012-06-22 Roasted Marshmallows [169][170]
2.15.0 2012-03-30 Easter Beagle [171][172]
2.14.2 2012-02-29 Gift-Getting Season See It's the Easter Beagle, Charlie Brown[173][174]
2.14.1 2011-12-22 December Snowflakes [175][176]
2.14.0 2011-10-31 Great Pumpkin See It's the Great Pumpkin, Charlie Brown[177][178]
r-devel N/A Unsuffered Consequences [179][45]

See also

[edit]

Notes

[edit]
  1. ^This displays to standard error a listing of all the packages that tidyverse depends upon. It may also display warnings showing namespace conflicts, which may typically be ignored.

References

[edit]
  1. ^ abcMorandat, Frances; Hill, Brandon; Osvald, Leo; Vitek, Jan (11 June 2012). "Evaluating the design of the R language: objects and functions for data analysis". European Conference on Object-Oriented Programming. 2012: 104–131. doi:10.1007/978-3-642-31057-7_6. Retrieved 17 May 2016 – via SpringerLink.
  2. ^Peter Dalgaard (11 April 2025). "R 4.5.0 is released". Retrieved 11 April 2025.
  3. ^ ab"R - Free Software Directory". directory.fsf.org. Retrieved 26 January 2024.
  4. ^"R scripts". mercury.webster.edu. Retrieved 17 July 2021.
  5. ^"R Data Format Family (.rdata, .rda)". Loc.gov. 9 June 2017. Retrieved 17 July 2021.
  6. ^ abHornik, Kurt; The R Core Team (12 April 2022). "R FAQ". The Comprehensive R Archive Network. 3.3 What are the differences between R and S?. Archived from the original on 28 December 2022. Retrieved 27 December 2022.
  7. ^"Introduction". The Julia Manual. Archived from the original on 20 June 2018. Retrieved 5 August 2018.
  8. ^"Comparison with R". pandas Getting started. Retrieved 15 July 2024.
  9. ^Giorgi, Federico M.; Ceraolo, Carmine; Mercatelli, Daniele (27 April 2022). "The R Language: An Engine for Bioinformatics and Data Science". Life. 12 (5): 648. Bibcode:2022Life...12..648G. doi:10.3390/life12050648. PMC 9148156. PMID 35629316.
  10. ^Ihaka, Ross. "The R Project: A Brief History and Thoughts About the Future"(PDF). p. 12. Archived(PDF) from the original on 28 December 2022. Retrieved 27 December 2022. We set a goal of developing enough of a language to teach introductory statistics courses at Auckland.
  11. ^Hornik, Kurt; The R Core Team (12 April 2022). "R FAQ". The Comprehensive R Archive Network. 2.13 What is the R Foundation?. Archived from the original on 28 December 2022. Retrieved 28 December 2022.
  12. ^"Index of /datasets". lib.stat.cmu.edu. Retrieved 5 September 2024.
  13. ^Ihaka, Ross. "R: Past and Future History"(PDF). p. 4. Archived(PDF) from the original on 28 December 2022. Retrieved 28 December 2022.
  14. ^Ihaka, Ross (5 December 1997). "New R Version for Unix". stat.ethz.ch. Archived from the original on 12 February 2023. Retrieved 12 February 2023.
  15. ^Ihaka, Ross. "The R Project: A Brief History and Thoughts About the Future"(PDF). p. 18. Archived(PDF) from the original on 28 December 2022. Retrieved 27 December 2022.
  16. ^Wickham, Hadley; Cetinkaya-Rundel, Mine; Grolemund, Garrett (2023). R for Data Science, Second Edition. O'Reilly. p. xvii. ISBN 978-1-492-09740-2.
  17. ^"Quarto". Quarto. Retrieved 5 September 2024.
  18. ^Chambers, John M. (2020). "S, R, and Data Science". The R Journal. 12 (1): 462–476. doi:10.32614/RJ-2020-028. ISSN 2073-4859. The R language and related software play a major role in computing for data science. ... R packages provide tools for a wide range of purposes and users.
  19. ^Davies, Tilman M. (2016). "Installing R and Contributed Packages". The Book of R: A First Course in Programming and Statistics. San Francisco, California: No Starch Press. p. 739. ISBN 9781593276515.
  20. ^ abHornik, Kurt (2012). "The Comprehensive R Archive Network". WIREs Computational Statistics. 4 (4): 394–398. doi:10.1002/wics.1212. ISSN 1939-5108. S2CID 62231320.
  21. ^Kurt Hornik (23 April 1997). "Announce: CRAN". r-help. Wikidata Q101068595..
  22. ^"The Status of CRAN Mirrors". cran.r-project.org. Retrieved 16 October 2024.
  23. ^"CRAN - Contributed Packages". cran.r-project.org. Retrieved 16 October 2024.
  24. ^"R-Forge: Welcome". r-forge.r-project.org. Retrieved 5 September 2024.
  25. ^"The Omega Project for Statistical Computing". www.omegahat.net. Retrieved 5 September 2024.
  26. ^"Build software better, together". GitHub. Retrieved 5 September 2024.
  27. ^Wickham, Hadley (2014). "Tidy Data" (PDF). Journal of Statistical Software. 59 (10). doi:10.18637/jss.v059.i10.
  28. ^ abWickham, Hadley; Cetinkaya-Rundel, Mine; Grolemund, Garrett (2023). R for Data Science, Second Edition. O'Reilly. ISBN 978-1-492-09740-2.
  29. ^"R for macOS". cran.r-project.org. Retrieved 5 September 2024.
  30. ^"IDE/Editor para Linguagem R | Tinn-R - Home". Tinn-R (in Brazilian Portuguese). Retrieved 5 September 2024.
  31. ^Talbot, Justin; DeVito, Zachary; Hanrahan, Pat (1 January 2012). "Riposte: A trace-driven compiler and parallel VM for vector code in R". Proceedings of the 21st international conference on Parallel architectures and compilation techniques. ACM. pp. 43–52. doi:10.1145/2370816.2370825. ISBN 9781450311823. S2CID 1989369.
  32. ^Jackson, Joab (16 May 2013). TIBCO offers free R to the enterprise. PC World. Retrieved 20 July 2015.
  33. ^"Looking to the future for R in Azure SQL and SQL Server". 30 June 2021. Retrieved 7 November 2021.
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  35. ^R Development Core Team. "Assignments with the = Operator". Retrieved 11 September 2018.
  36. ^Kabacoff, Robert (2012). "Quick-R: User-Defined Functions". statmethods.net. Retrieved 28 September 2018.
  37. ^Wickham, Hadley. "Advanced R - Functional programming - Closures". adv-r.had.co.nz.
  38. ^"NEWS". r-project.org.
  39. ^"R: R News". cran.r-project.org. Retrieved 14 March 2024.
  40. ^Wickham, Hadley; Çetinkaya-Rundel, Mine; Grolemund, Garrett (2023). "4 Workflow: code style". R for data science: import, tidy, transform, visualize, and model data (2nd ed.). Beijing; Sebastopol, CA: O'Reilly. ISBN 978-1-4920-9740-2. OCLC 1390607935.
  41. ^"Class Methods". Retrieved 25 April 2024.
  42. ^Monkman, Martin. Chapter 5 R Release Names | Data Science with R: A Resource Compendium.
  43. ^McGowan, Lucy D’Agostino (28 September 2017). "R release names". livefreeordichotomize.com. Retrieved 7 April 2024.
  44. ^r-hub/rversions, The R-hub project of the R Consortium, 29 February 2024, retrieved 7 April 2024
  45. ^ abcdDalgaard, Peter (15 July 2018). "What's in a name? 20 years of R release management"(video). YouTube. Retrieved 9 April 2024.
  46. ^"Read Peanuts by Charles Schulz on GoComics". www.gocomics.com. Retrieved 17 April 2025.
  47. ^"[Rd] R 4.5.0 is released". hypatia.math.ethz.ch. Retrieved 17 April 2025.
  48. ^"Read Peanuts by Charles Schulz on GoComics". www.gocomics.com. Retrieved 17 April 2025.
  49. ^"[Rd] R 4.4.3 is released". hypatia.math.ethz.ch. Retrieved 17 April 2025.
  50. ^Schulz, Charles (15 November 1957). "Peanuts by Charles Schulz for November 15, 1957 | GoComics.com". GoComics. Retrieved 6 January 2025.
  51. ^"[Rd] R 4.4.2 is released". stat.ethz.ch. Retrieved 26 December 2024.
  52. ^"Race for Your Life, Charlie Brown". IMDB. 3 August 1977. Retrieved 18 June 2024.
  53. ^"R 4.4.1 is released". stat.ethz.ch. Retrieved 18 June 2024.
  54. ^Schulz, Charles (29 June 1980). "Peanuts by Charles Schulz for June 29, 1980 | GoComics.com". GoComics. Retrieved 24 April 2024.
  55. ^"R 4.4.0 is released". stat.ethz.ch. Retrieved 24 April 2024.
  56. ^Schulz, Charles (29 June 1980). "Peanuts by Charles Schulz for June 29, 1980 | GoComics.com". GoComics. Retrieved 9 April 2024.
  57. ^"R 4.3.3 is released". hypatia.math.ethz.ch. Retrieved 7 April 2024.
  58. ^Schulz, Charles (31 October 1996). "Peanuts by Charles Schulz for October 31, 1996 | GoComics.com". GoComics. Retrieved 9 April 2024.
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Further reading

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