R is a programming language and software environment designed for statistical computing, data analysis and graphics. It combines an interactive programming language with facilities for manipulating data, numerical calculation, statistical modelling and visualisation.
The language is particularly strong for exploratory analysis and statistical research. Its package system makes the environment highly extensible, with additional software available for fields ranging from econometrics and bioinformatics to machine learning, spatial analysis and publication-quality graphics.
This is free and open source software.
Key Features
- Effective facilities for handling and storing vectors, factors, data frames and other data structures.
- Operators and functions for calculations on arrays and matrices.
- Linear and nonlinear statistical modelling.
- Generalised linear models and a broad collection of classical statistical tests.
- Time-series analysis and forecasting facilities.
- Classification, clustering and multivariate analysis.
- Formula notation provides a concise way to specify statistical models.
- Produces publication-quality plots with support for mathematical notation, multiple graphical devices and extensive customisation.
- Programming language includes conditionals, loops, functions, recursion and lexical scoping.
- Interactive console supports exploratory work, while scripts allow analyses to be automated and reproduced.
- Integrated help system provides documentation for functions, packages and datasets.
- Package mechanism extends the language with new statistical methods, data formats, graphics and specialist functionality.
- CRAN provides a large ecosystem of contributed packages.
- Packages can contain R code, compiled code, datasets, documentation and tests.
- Interfaces allow extensions to call code written in C, C++ and Fortran.
- Data import and export facilities cover common text formats and can be extended through packages to support databases, spreadsheets and specialist formats.
- Supports workspaces, saved objects and serialisation of R data structures.
- Debugging, tracing and profiling tools help developers inspect and optimise R programs.
- Suitable for interactive statistics, research, teaching, data science and development of reusable analytical software.
- Cross-platform support – runs on Linux, macOS, and Windows.
Website: www.r-project.org
Support:
Developer: R Core Team
License: GNU General Public License v2.0 or v3.0
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| Data Mining Software | |
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| Statistical Analysis Tools | |
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