R – software environment for statistical computing and graphics

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).

Website: www.r-project.org
Support: Manuals
Developer: R Development Core Team
License: GNU GPL v2

Return to Scientific Home Page | Return to Econometric Home Page | Return to Data Mining Home Page | Return to Statistical Analysis Home Page


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