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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).
Download as PDF; Printable version; In other projects ... RGtk2 Package on CRAN; github ... Statistics; Cookie statement ...
Bibliometrix is a package for the R statistical programming language for quantitative research in scientometrics and bibliometrics. [1]Bibliometrics is the application of quantitative analysis and statistics to publications such as journal articles and their accompanying citation counts.
A software repository, or repo for short, is a storage location for software packages. Often a table of contents is also stored, along with metadata. A software repository is typically managed by source or version control, or repository managers. Package managers allow automatically installing and updating repositories, sometimes called "packages".
"A Short Preview of Free Statistical Software Packages for Teaching Statistics to Industrial Technology Majors" (PDF). Journal of Industrial Technology. 21 (2). Archived from the original (PDF) on October 25, 2005.
As an example, R packages tnet, [6] igraphtosonia [7] and cccd [8] depend on igraph R package. Users can use igraph on many operating systems. The C library and R and Python packages need the respective software, otherwise igraph is portable. The C library of igraph is well documented [9] as well as the R package [10] and the Python package [11]
Stata – comprehensive statistics package; StatCrunch – comprehensive statistics package, originally designed for college statistics courses; Statgraphics – general statistics package; Statistica – comprehensive statistics package; StatsDirect – statistics package designed for biomedical, public health and general health science uses
LISREL (linear structural relations) is a proprietary statistical software package used in structural equation modeling (SEM) for manifest and latent variables. It requires a "fairly high level of statistical sophistication".