Programming Tutorial: August 2015

Thursday, August 27, 2015

S programming language.

S is a statistical programming language developed primarily by John Chambers and (in earlier versions) Rick Becker and Allan Wilks of Bell Laboratories. The aim of the language, as expressed by John Chambers, is "to turn ideas into software, quickly and faithfully". The two modern implementations of S are R, part of the GNU free software project, and S-PLUS.

"Old S" S is one of several statistical computing languages that were designed at Bell Laboratories, and first took form between 1975–1976. Up to that time, much of the statistical computing was done by directly calling Fortran subroutines; however, S was designed to offer an alternate and more interactive approach. Early design decisions that hold even today include interactive graphics devices (printers and character terminals at the time), and providing easily accessible documentation for the functions. The first working version of S was built in 1976, and operated on the GCOS operating system. At this time, S was unnamed, and suggestions included Interactive SCS (ISCS), Statistical Computing System, and Statistical Analysis System (which was already taken: see SAS System). The name 'S' (used with single quotation marks, until 1979) was chosen, as it has the common letter used in statistical computing, and is consistent with other programming languages designed from the same institution at the time (namely the C programming language). When UNIX/32V was ported to the (then new) 32-bit DEC VAX, computing on the Unix platform became feasible for S. In late 1979, S was ported from GCOS to UNIX, which would become the new primary platform. In 1980 the first version of S was distributed outside Bell Laboratories and in 1981 source versions were made available. In 1984 two books were published by the research team at Bell Laboratories: S: An Interactive Environment for Data Analysis and Graphics (1984 Brown Book) and Extending the S System. Also, in 1984 the source code for S became licensed through AT&T Software Sales for education and commercial purposes.

"New S" By 1988, many changes were made to S and the syntax of the language. The New S Language (1988 Blue Book) was published to introduce the new features, such as the transition from macros to functions and how functions can be passed to other functions (such as apply). Many other changes to the S language were to extend the concept of "objects", and to make the syntax more consistent (and strict). However, many users found the transition to New S difficult, since their macros needed to be rewritten. Many other changes to S took hold, such as the use of X11 and PostScript graphics devices, rewriting many internal functions from Fortran to C, and the use of double precision (only) arithmetic. The New S language is very similar to that used in modern versions of S-PLUS and R. In 1991, Statistical Models in S (1991 White Book) was published, which introduced the use of formula-notation (which use the '~' operator), data frame objects, and modifications to the use of object methods and classes.

R programming language.

R is a programming language and software environment for statistical computing and graphics. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. Polls, surveys of data miners, and studies of scholarly literature databases show that R's popularity has increased substantially in recent years.

R is an implementation of the S programming language combined with lexical scoping semantics inspired by Scheme. S was created by John Chambers while at Bell Labs. There are some important differences, but much of the code written for S runs unaltered. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team, of which Chambers is a member. R is named partly after the first names of the first two R authors and partly as a play on the name of S. R is a GNU project. The source code for the R software environment is written primarily in C, Fortran, and R. R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems. R uses a command line interface; there are also several graphical front-ends for it.
R and its libraries implement a wide variety of statistical and graphical techniques, including linear and nonlinear modeling, 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, C, C++, and Fortran code can be linked and called at run time. Advanced users can write C, C++, Java, .NET or Python code to manipulate R objects directly. 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 stronger object-oriented programming facilities than most statistical computing languages. Extending R is also eased by its lexical scoping rules. 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. R has its own LaTeX-like documentation format, which is used to supply comprehensive documentation, both on-line in a number of formats and in hard copy.