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Wednesday, 24 October 2018

About R proramming by MD

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Posted as MD
R is a programming language and freesoftware environment for statistical computing and graphics supported by the R Foundation for Statistical Computing.[6] The R language is widely used among statisticiansand data miners for developing statistical software[7] and data analysis.[8] Polls, data mining surveys and studies of scholarly literature databases, show substantial increases in popularity in recent years.[9] As of August 2018, R ranks 18th in the TIOBE index, a measure of popularity of programming languages.[10]


R is an implementation of the S programming language combined with lexical scopingsemantics, inspired by Scheme.[15] S was created by John Chambers in 1976, while atBell Labs. There are some important differences, but much of the code written for S runs unaltered.[16]
R was created by Ross Ihaka and Robert Gentleman[17] at the University of Auckland, New Zealand, and currently developed by theR Development Core Team (of which Chambers is a member).[18] R is named partly after the first names of the first two R authors and partly as a play on the name of S.[19] The project was conceived in 1992, with an initial version released in 1995 and a stable beta version in 2000.[20][21][22]

Statistical featuresEdit

R and its libraries implement a wide variety of statistical and graphical techniques, includinglinear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, and others. R is easily extensible through functions and extensions, and the R community is noted for its active contributions in terms of packages. Many of R's standard functions are written in R itself, which makes it easy for users to follow the algorithmic choices made. For computationally intensive tasks, CC++, andFortran code can be linked and called at run time. Advanced users can write C, C++,[23]Java,[24] .NET[25] or Python code to manipulate R objects directly.[26] R is highly extensible through the use of user-submitted packages for specific functions or specific areas of study. Due to its S heritage, R has strongerobject-oriented programming facilities than most statistical computing languages. Extending R is also eased by its lexical scoping rules.[27]
Another strength of R is static graphics, which can produce publication-quality graphs, including mathematical symbols. Dynamic and interactive graphics are available through additional packages.[28]
R has Rd, its own LaTeX-like documentation format, which is used to supply comprehensive documentation, both online in a number of formats and in hard copy.[29]

R has vibrant and active local communities worldwide for users to network, share ideas and learn.[69][70]
There are regular R-user meetups[71] and a more focused R-Ladies[72] group

R logo.svg
Designed byRoss Ihaka and Robert Gentleman
DeveloperR Core Team[1]
First appearedAugust 1993; 25 years ago[2]

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