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  2. R package - Wikipedia

    https://en.wikipedia.org/wiki/R_package

    R logo. R packages are extensions to the R statistical programming language.R packages contain code, data, and documentation in a standardised collection format that can be installed by users of R, typically via a centralised software repository such as CRAN (the Comprehensive R Archive Network).

  3. RGtk2 - Wikipedia

    https://en.wikipedia.org/wiki/RGtk2

    RGtk2 is a set of R wrappers for the GTK+ graphical user interface library. RGtk2 is free software and licensed under ... RGtk2 Package on CRAN; github This page ...

  4. R (programming language) - Wikipedia

    https://en.wikipedia.org/wiki/R_(programming_language)

    R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.

  5. rnn (software) - Wikipedia

    https://en.wikipedia.org/wiki/Rnn_(software)

    The RStudio CRAN mirror download logs [11] show that the package is downloaded on average about 2,000 per month from those servers , [12] with a total of over 100,000 downloads since the first release, [13] according to RDocumentation.org, this puts the package in the 15th percentile of most popular R packages .

  6. RStudio - Wikipedia

    https://en.wikipedia.org/wiki/RStudio

    RStudio IDE (or RStudio) is an integrated development environment for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser.

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  8. Jamovi - Wikipedia

    https://en.wikipedia.org/wiki/Jamovi

    jamovi is an open source graphical user interface for the R programming language. [3] It is used in statistical research, especially as a tool for ANOVA (analysis of variance) and to understand statistical inference. [4] [5] It also can be used for linear regression, [6] mixed models and Bayesian models. [7]

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