If a user types 2+2 at the R command prompt and presses enter, the computer replies with 4. R is an interpreted language users can access it through a command-line interpreter. Another of R's strengths is static graphics it can produce publication-quality graphs that include mathematical symbols. For computationally intensive tasks, C, C++, and Fortran code can be linked and called at run time. R and its libraries implement various statistical techniques, including linear, generalized linear and nonlinear modeling, classical statistical tests, spatial and time-series analysis, classification, clustering, and others. Instead, a scalar is represented as a length-one vector. Data frames contain a list of vectors of the same length, plus a unique set of row names. Lists serve as collections of objects that do not necessarily have the same data type. The special case of an array with two dimensions is called a matrix. R supports array arithmetics and in this regard is like languages such as APL and MATLAB. That is, given an ordered collection of dimensions, one fills in values along the first dimension first, then fills in one-dimensional arrays across the second dimension, and so on. Vectors are ordered collections of values and can be mapped to arrays of one or more dimensions in a column major order. R's data structures include vectors, arrays, lists, data frames and environments. In April 2003, the R Foundation was founded as a non-profit organization to provide further support for the R project. Stefano Iacus, Guido Masarotto, Heiner Schwarte, Seth Falcon, Martin Morgan, and Duncan Murdoch were members. As of January 2022, it consists of Chambers, Gentleman, Ihaka, and Mächler, plus statisticians Douglas Bates, Peter Dalgaard, Kurt Hornik, Michael Lawrence, Friedrich Leisch, Uwe Ligges, Thomas Lumley, Sebastian Meyer, Paul Murrell, Martyn Plummer, Brian Ripley, Deepayan Sarkar, Duncan Temple Lang, Luke Tierney, and Simon Urbanek, as well as computer scientist Tomas Kalibera. The R Core Team was formed in 1997 to further develop the language. As of December 2022, it has 103 mirrors and 18,976 contributed packages. CRAN originally had three mirrors and 12 contributed packages. Its name and scope mimics the Comprehensive TeX Archive Network and the Comprehensive Perl Archive Network. The Comprehensive R Archive Network (CRAN) was founded in 1997 by Kurt Hornik and Fritz Leisch to host R's source code, executable files, documentation, and user-created packages. The first official 1.0 version was released on 29 February 2000. R officially became a GNU project on 5 December 1997 when version 0.60 released. Mailing lists for the R project began on 1 April 1997 preceding the release of version 0.50. In June 1995, statistician Martin Mächler convinced Ihaka and Gentleman to make R free and open-source under the GNU General Public License. Ihaka and Gentleman first shared binaries of R on the data archive StatLib and the s-news mailing list in August 1993. The name of the language comes from being an S language successor and the shared first letter of the authors, Ross and Robert. The language took heavy inspiration from the S programming language with most S programs able to run unaltered in R as well as from Scheme's lexical scoping allowing for local variables. R was started by professors Ross Ihaka and Robert Gentleman as a programming language to teach introductory statistics at the University of Auckland. Multiple third-party graphical user interfaces are also available, such as RStudio, an integrated development environment, and Jupyter, a notebook interface. Precompiled executables are provided for various operating systems. It is written primarily in C, Fortran, and R itself (partially self-hosting). The official R software environment is an open-source free software environment released as part of the GNU Project and available under the GNU General Public License. As of April 2023, R ranks 16th in the TIOBE index, a measure of programming language popularity, in which the language peaked in 8th place in August 2020. The core R language is augmented by a large number of extension packages containing reusable code and documentation.Īccording to user surveys and studies of scholarly literature databases, R is one of the most commonly used programming languages in data mining. Created by statisticians Ross Ihaka and Robert Gentleman, R is used among data miners, bioinformaticians and statisticians for data analysis and developing statistical software. R is a programming language for statistical computing and graphics supported by the R Core Team and the R Foundation for Statistical Computing.
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