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The easystats collection of open source R packages was created in 2019 and primarily includes tools dedicated to the post-processing of statistical models. [1] [2] As of May 2022, the 10 packages composing the easystats ecosystem have been downloaded more than 8 million times, and have been used in more than 1000 scientific publications.
One of the first completely free to use and open source statistical software was R, first released in 2000. [1] Some of the free software packages are from governments, for example Epi Info, which is from CDC [4] (Centers for Disease Control and Prevention). Some other software packages are from smaller or independent organizations or universities.
In addition, users can install modules from a library of community created open source add-on modules to extend the package's capabilities. [10] [11] These modules are written in the R programming language and make use of the jmv [12] and jmvtools [13] libraries to create the interface and display code. Numerous modules exist and can be ...
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).
The S-PLUS FinMetrics software package was developed for econometric time series analysis. [1] Due to the increasing popularity of the open source S successor R, TIBCO Software released the TIBCO Enterprise Runtime for R (TERR) as an alternative R interpreter. [2] It is available on Windows and UNIX operating systems. [3]
React (also known as React.js or ReactJS) is a free and open-source front-end JavaScript library [4] [5] for building user interfaces based on components by Facebook Inc. It is maintained by Meta (formerly Facebook) and a community of individual developers and companies.
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Unlike analytics products offered by SAS Institute, R does not natively handle datasets larger than main memory.In 2010 Revolution Analytics introduced ScaleR, a package for Revolution R Enterprise designed to handle big data through a high-performance disk-based data store called XDF (not related to IBM's Extensible Data Format) and high performance computing across large clusters. [18]