S language
Similar to Python and Scheme, S is a high level of programming language. S is very much compatible with the rapid development of statistical applications. The interactive feature of data analysis was considered to design S language.
In 1976, Joan Chambers and Rick Becker and Allan Wilks of Bell Laboratories developed the S programing language. The name “S” was chosen from the common letter of two suggested names: Interactive SCS (ISCS), Statistical Computing System, and Statistical Analysis System. In 1988 New S was released after revising many syntaxes of S language. The latest version of S language is called S4. It included advance object oriented features and was released in1998.
S Plus and R are the two major implementation of S language. The language of S Plus and R is very much similar to new S. S plus is the commercial version of S, on the other hand R is the open source version.
One of the major drawback of S is that it can handle only a small amount of data set.
R language
R is a very popular and widely used programing language for statistical applications. It is considered as a dialect of S language. The popularity of R has been increasing dramatically. Currently R ranks 8th in the TIOBE index.
R was developed by Ross Ihaka and Robert Gentleman at the university of Auckland in New Zealand. Currently, R is developed by R Development Core Team. John Chambers, one of the member of R team won the ACM Software Systems award for R statistics and graphic environment. Although the R project started in 1992, the stable beta version became in 2000.
R language can be used for developing statistical software and data analysis.
R can be used in several statistical and graphical techniques such as classification, clustering, time-series analysis, classical statistical tests, linear and nonlinear modeling.
In spite of the differences, much of the code of S applies to R without any change.
C, C++, Java, NET or Python code can also be used to manipulate R objects. Static, Dynamic and interactive graphics are included in R which enable publication quality graphs.
The core packages of R is embedded with the installation of R. In addition, more than 11,000 packages are also available at the Comprehensive R Archive Network (CRAN),Bioconductor, Omegahat,GitHub, and other repositories.
R Studio is one of the commonly used graphical environment for R. R Tools for Visual Studio is another similar interface as R Studio.
R is a free and open source software and it is supported by the R community members.