Pakiet: r-recommended (4.3.3-3)

[ Pakiet źródłowy: r-base  ]

GNU R collection of recommended packages [metapackage]

R is a system for statistical computation and graphics. It consists of a language plus a run-time environment with graphics, a debugger, access to certain system functions, and the ability to run programs stored in script files.

The design of R has been heavily influenced by two existing languages: Becker, Chambers & Wilks' S and Sussman's Scheme. Whereas the resulting language is very similar in appearance to S, the underlying implementation and semantics are derived from Scheme.

The core of R is an interpreted computer language which allows branching and looping as well as modular programming using functions. Most of the user-visible functions in R are written in R. It is possible for the user to interface to procedures written in the C, C++, or FORTRAN languages for efficiency, and many of R's core functions do so. The R distribution contains functionality for a large number of statistical procedures and underlying applied math computations. There is also a large set of functions which provide a flexible graphical environment for creating various kinds of data presentations.

Additionally, several thousand extension "packages" are available from CRAN, the Comprehensive R Archive Network, many also as Debian packages, named 'r-cran-<name>'.

This Debian package is now a metapackage that depends on a set of packages that are recommended by the upstream R core team as part of a complete R distribution, and distributed along with the source of R itself, as well as directly via the CRAN network of mirrors. This set comprises the following packages (listed in their upstream names):

 - KernSmooth: Functions for kernel smoothing for Wand & Jones (1995)
 - Matrix: Classes and methods for dense and sparse matrices and
   operations on them using Lapack and SuiteSparse
 - MASS, class, nnet and spatial: packages from Venables and Ripley,
   `Modern Applied Statistics with S' (4th edition).
 - boot: Bootstrap R (S-Plus) Functions from the book "Bootstrap Methods
   and Their Applications" by A.C. Davison and D.V. Hinkley (1997).
 - cluster: Functions for clustering (by Rousseeuw et al.)
 - codetools: Code analysis tools for R
 - foreign: Read data stored by Minitab, S, SAS, SPSS, Stata, ...
 - lattice: Implementation of Trellis (R) graphics
 - mgcv: Multiple smoothing parameter estimation and GAMs by GCV
 - nlme: Linear and nonlinear mixed effects models
 - rpart: Recursive partitioning and regression trees
 - survival: Survival analysis, including penalised likelihood.

Znaczniki: Rozwój oprogramowania: Rozwijanie w języku GNU R, Dziedzina: Statystyka, Rola: Pakiet atrapa, role::metapackage, suite::gnu

Inne pakiety związane z r-recommended

• dep: r-base-core (>= 4.3.3-3)

  GNU R core of statistical computation and graphics system

• dep: r-cran-boot (>= 1.2.19)

  GNU R package for bootstrapping functions from Davison and Hinkley

• dep: r-cran-class

  GNU R package for classification

• dep: r-cran-cluster (>= 1.9.6-2)

  GNU R package for cluster analysis by Rousseeuw et al

• dep: r-cran-codetools

  GNU R package providing code analysis tools

• dep: r-cran-foreign (>= 0.7-2)

  GNU R package to read/write data from other stat. systems

• dep: r-cran-kernsmooth (>= 2.2.14)

  GNU R package for kernel smoothing and density estimation

• dep: r-cran-lattice (>= 0.10.11)

  GNU R package for 'Trellis' graphics

• dep: r-cran-mass

  GNU R package of Venables and Ripley's MASS

• dep: r-cran-matrix

  GNU R package of classes for dense and sparse matrices

• dep: r-cran-mgcv (>= 1.1.5)

  GNU R package for multiple parameter smoothing estimation

• dep: r-cran-nlme (>= 3.1.52)

  GNU R package for (non-)linear mixed effects models

• dep: r-cran-nnet

  GNU R package for feed-forward neural networks

• dep: r-cran-rpart (>= 3.1.20)

  GNU R package for recursive partitioning and regression trees

• dep: r-cran-spatial

  GNU R package for spatial statistics

• dep: r-cran-survival (>= 2.13.2-1)

  GNU R package for survival analysis

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