R
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 3.0.0
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Price
Free to download
Size
24.3MB
License
GNU GPL v2
Developer
R Development Core Team
Website
www.r-project.org
System Requirements
Support
Sites:
R
Manuals, Wiki,
FAQ,
Newsletter,
Mailing
List, R
Graph Gallery, Kickstarting
R,
Journal of
Statistical
Software, Technical
Notes on the R programming language, R_note,
R
Tips, Using
R for
Psychology Research,
R
Applications
Selected
Reviews:
Sciviews.org, dmreview,
Statland.org
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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).
There are a number of excellent graphical frontends for R. You
can view our favourites at 7
of the Best Free Graphical User Interfaces for R.
Return
to Scientific Home Page | Return
to Econometric Home Page | Return
to Data Mining Home Page | Return
to Statistical Analysis Home Page
R also features in our 'Linux
Equivalents to Windows Software' section. The category
selector below allows you to filter the different types of software
included in that separate article.
Last Updated Saturday, April 13 2013 @ 06:32 PM EDT
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