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 General Public License v2.0
Related Software
| Econometric Software | |
|---|---|
| R | Statistical computation and graphics system |
| gretl | Regression, Econometric and Time-Series Library |
| Grocer | Econometric toolbox for Scilab, software similar to Gauss and Matlab |
| GeoDa | Exploratory data analysis and spatial regression |
| Draco | Econometrics and statistics package |
| gbutils | Set of command line utilities for the manipulation and statistical analysis of data |
Read our verdict in the software roundup.
| Data Mining Software | |
|---|---|
| R | Software environment for statistical computing and graphics |
| MOA | Software environment for data stream mining |
| Orange | Component-based framework for machine learning and data mining |
| astroML | Python module for machine learning and data mining |
| ROOT | Aimed at solving the data analysis challenges of high-energy physics |
| ELKI | Data mining software framework developed for use in research and teaching |
| DataMelt | Full-featured data-analysis framework for scientists, engineers and students |
| KNIME | Konstanz Information Miner |
| Weka | Waikato Environment for Knowledge Analysis |
| RapidMiner | Knowledge discovery in databases, machine learning, and data mining |
| Rattle | Gnome cross platform GUI for Data Mining using R |
Read our verdict in the software roundup.
| Statistical Analysis Tools | |
|---|---|
| RStudio | Professional software for R with code editor, debugging & visualization tools |
| R | Environment for statistical computing and graphics |
| gretl | Regression, Econometric and Time-Series Library |
| ROOT | Solves the data analysis challenges of high-energy physics |
| SOFA Statistics | Extremely user-friendly statistics, analysis and reporting package |
| PSPP | Free replacement of the proprietary program, SPSS |
| JASP | Statistical package for both Bayesian and Frequentist statistical methods |
| jamovi | Real-time statistical spreadsheet |
Read our verdict in the software roundup.
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