Last Updated on July 13, 2023
The R Project for Statistical Computing (R) is a free software environment for statistical computing and graphics.
R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible.
The S language is often the vehicle of choice for research in statistical methodology, and econometrics, and R provides an Open Source route to participation in that activity.
R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes:
- An effective data handling and storage facility.
- A suite of operators for calculations on arrays, in particular matrices.
- A large, coherent, integrated collection of intermediate tools for data analysis.
- Graphical facilities for data analysis and display either on-screen or on hardcopy, and
- A well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.
One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed.
R, like S, is designed around a true computer language, and it allows users to add additional functionality by defining new functions. Much of the system is itself written in the R dialect of S, which makes it easy for users to follow the algorithmic choices made.
Although R is mostly used by statisticians who need an environment for statistical computation and software development, it can also be used as a general matrix calculation toolbox with comparable benchmark results to Octave and its proprietary counterpart, MATLAB (version < 7).
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