R (programming language) facts for kids
|Paradigms||Multi-paradigm: Array programming, object-oriented, imperative, functional|
|Designed by||Ross Ihaka and Robert Gentleman (statistician)|
|Developer||R Core Team|
|First appeared||August 1993|
|Stable release||4.0.2 ("Taking Off Again") / June 22, 2020|
|License||GNU GPL v2|
R is a programming language and free software environment for statistics. R is a language built for a specific purpose. It is strictly designed for statistical analysis. The algorithms for many statistical models are devised in R. Precisely R is the language of Statistical Analyzers. It’s an open source and the best suite for the statisticians to develop statistical softwares. R is putting utmost efforts to walk parallelly to Python.
Usage in other areas
The R language was originally made for statistics. But today, it is also used in many scientific fields including ecology.
A list of changes in R releases is maintained in various "news" files at CRAN (Comprehensive R Archive Network). Some highlights are listed below for several major releases.
|0.16||This is the last test version.|
|0.49||1997-04-23||This is the oldest source release which is currently available on CRAN. CRAN is started on this date, with 3 mirrors that initially hosted 12 packages.|
|0.60||1997-12-05||R becomes an official part of the GNU Project. The code is hosted and maintained on CVS.|
|0.65.1||1999-10-07||First versions of update.packages and install.packages functions for downloading and installing packages from CRAN.|
|1.0||2000-02-29||The developers declared that it is stable enough for production use.|
|1.4||2001-12-19||S4 methods are introduced and the first version for Mac OS X is made available soon after.|
|1.8||2003-10-08||Introduced a flexible condition handling mechanism for signalling and handling condition objects.|
|2.0||2004-10-04||Introduced fast loading of data with minimal expense of system memory.|
|2.1||2005-04-18||Support for UTF-8 encoding. They also started of internationalization and localization for different languages.|
|2.6.2||2008-02-08||Last version to support Windows 95, 98, Me and NT 4.0|
|2.11||2010-04-22||Support for Windows 64 bit systems.|
|2.12.2||2011-02-25||Last version to support Windows 2000|
|2.13||2011-04-14||Adding a new compiler function that allows speeding up functions by converting them to byte-code.|
|2.14||2011-10-31||Added mandatory namespaces for packages. Added a new parallel package.|
|2.15||2012-03-30||New load balancing functions. Improved serialization speed for long vectors.|
|3.0.0||2013-04-03||Support for numeric index values 231 and larger on 64 bit systems.|
|3.3.3||2017-03-06||Last version to support Microsoft Windows XP.|
|3.4.0||2017-04-21||Just-in-time compilation (JIT) of functions and loops to byte-code enabled by default.|
|3.5.0||2018-04-23||Packages byte-compiled on installation by default. Compact internal representation of integer sequences. Added a new serialization format to support compact internal representations.|
R has local communities worldwide for users to share ideas and learn.
There are a growing number of R events bringing its users together, such as conferences (e.g. useR!, WhyR?, conectaR, SatRdays) and other meetups.
The official annual gathering of R users is called "useR!". The first such event was useR! 2004 in May 2004, Vienna, Austria. After skipping 2005, the useR! conference has been held annually. Subsequent conferences have included:
- useR! 2006, Vienna, Austria
- useR! 2007, Ames, Iowa, USA
- useR! 2008, Dortmund, Germany
- useR! 2009, Rennes, France
- useR! 2010, Gaithersburg, Maryland, USA
- useR! 2011, Coventry, United Kingdom
- useR! 2012, Nashville, Tennessee, USA
- useR! 2013, Albacete, Spain
- useR! 2014, Los Angeles, California, USA
- useR! 2015, Aalborg, Denmark
- useR! 2016, Stanford, California, USA
- useR! 2017, Brussels, Belgium
- useR! 2018, Brisbane, Australia
- useR! 2019, Toulouse, France
Future conferences planned are as follows:
The R Journal
The R Journal is the open access refereed journal of the R project. It features articles on the use and development of the R language.
The following examples illustrate the basic syntax of the language and use of the command-line interface.
In R, the generally preferred assignment operator is an arrow made from two characters
= can be used instead.
> x <- 1:6 # Create vector. > y <- x^2 # Create vector by formula. > print(y) # Print the vector’s contents.  1 4 9 16 25 36 > mean(y) # Arithmetic mean of vector.  15.16667 > var(y) # Sample variance of vector.  178.9667 > model <- lm(y ~ x) # Linear regression model y = A + B * x. > print(model) # Print the model’s results. Call: lm(formula = y ~ x) Coefficients: (Intercept) x -9.333 7.000 > summary(model) # Display an in-depth summary of the model. Call: lm(formula = y ~ x) Residuals: 1 2 3 4 5 6 3.3333 -0.6667 -2.6667 -2.6667 -0.6667 3.3333 Coefficients: 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 ‘ ’ 1 Residual standard error: 3.055 on 4 degrees of freedom Multiple R-squared: 0.9583, Adjusted R-squared: 0.9478 F-statistic: 91.88 on 1 and 4 DF, p-value: 0.000662 > par(mfrow = c(2, 2)) # Create a 2 by 2 layout for figures. > plot(model) # Output diagnostic plots of the model.
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