Source: r-base
Section: math
Priority: optional
Maintainer: Dirk Eddelbuettel <edd@debian.org>
Uploaders: Douglas Bates <bates@stat.wisc.edu>
Standards-Version: 3.7.2
Build-Depends: gcc (>= 4:4.0), gfortran (>= 4.0.2), refblas3-dev | atlas3-base-dev, tcl8.4-dev, tk8.4-dev, bison, groff-base, libncurses5-dev, libreadline5-dev, debhelper (>= 3.0.0), texi2html, texinfo (>= 4.1-2), libbz2-dev, libpcre3-dev, tetex-bin, tetex-extra, xpdf-reader, zlib1g-dev, libpng12-dev, libjpeg62-dev, libx11-dev, libxt-dev, x-dev

Package: r-base
Architecture: all
Depends: r-base-core (>= ${Source-Version}), r-recommended (= ${Source-Version})
Recommends: r-base-html, r-base-latex
Suggests: ess, r-doc-info | r-doc-pdf | r-doc-html
Description: GNU R statistical computing language and environment
 R is `GNU S' - A language and environment for statistical computing
 and graphics. R is similar to the award-winning S system, which was
 developed at Bell Laboratories by John Chambers et al. It provides a
 wide variety of statistical and graphical techniques (linear and
 nonlinear modelling, statistical tests, time series analysis,
 classification, clustering, ...).
 .
 R is designed as a true computer language with control-flow
 constructions for iteration and alternation, and it allows users to
 add additional functionality by defining new functions. For
 computationally intensive tasks, C, C++ and Fortran code can be
 linked and called at run time.
 .
 S is the statistician's Matlab and R is to S what Octave is to Matlab.
 .
 This package is a meta-package which eases the transition from the 
 pre-1.5.0 package setup with its larger r-base package. Once installed, it 
 can be safely removed and apt-get will automatically upgrade its components
 during future upgrades.  Providing this packages gives a way to users to 
 then only install r-base-core (but not, say, r-base-latex) if they so desire.

Package: r-base-core
Architecture: any
Depends: ${perl:Depends}, zlib-bin, libpaper-utils, ${shlibs:Depends}
Replaces: r-base (<= 1.4.1-1), r-recommended (<< 1.9.0), r-gnome (<= 2.3.1)
Provides:  r-gnome
Conflicts:  r-gnome
Recommends: r-recommended, r-base-dev
Suggests: ess, r-doc-info | r-doc-pdf | r-doc-html, r-mathlib, r-base-html | r-base-latex
Description: GNU R core of statistical computing language and environment
 R is `GNU S' - A language and environment for statistical computing
 and graphics. R is similar to the award-winning S system, which was
 developed at Bell Laboratories by John Chambers et al. It provides a
 wide variety of statistical and graphical techniques (linear and
 nonlinear modelling, statistical tests, time series analysis,
 classification, clustering, ...).
 .
 R is designed as a true computer language with control-flow
 constructions for iteration and alternation, and it allows users to
 add additional functionality by defining new functions. For
 computationally intensive tasks, C, C++ and Fortran code can be
 linked and called at run time.
 .
 S is the statistician's Matlab and R is to S what Octave is to Matlab.
 .
 This package provides the core GNU R system from which only the optional
 documentation packages r-base-html, r-base-latex, r-doc-html, r-doc-pdf 
 and r-doc-info have been split off to somewhat reduce the size of this 
 package. 

Package: r-base-dev
Architecture: all
Section: devel
Depends: r-base-core (>= ${Source-Version}), refblas3-dev | atlas3-base-dev | libblas-3.so, build-essential, gfortran (>= 4.0.2), gcc (>= 4:4.0), g++ (>= 4:4.0), libncurses5-dev, libreadline5-dev, libjpeg62-dev, libpcre3-dev, libpng12-dev, zlib1g-dev, libbz2-dev
Description: GNU R installation of auxiliary GNU R packages 
 R is `GNU S' - A language and environment for statistical computing
 and graphics. R is similar to the award-winning S system, which was
 developed at Bell Laboratories by John Chambers et al. It provides a
 wide variety of statistical and graphical techniques (linear and
 nonlinear modelling, statistical tests, time series analysis,
 classification, clustering, ...).
 .
 R is designed as a true computer language with control-flow
 constructions for iteration and alternation, and it allows users to
 add additional functionality by defining new functions. For
 computationally intensive tasks, C, C++ and Fortran code can be
 linked and called at run time.
 .
 This packages ensures that other Debian packages needed for installation of
 some auxiliary R packages are installed.

Package: r-mathlib
Architecture: any
Depends: 
Recommends: r-base-core (= ${Source-Version}), r-base-dev (= ${Source-Version})
Description: GNU R standalone mathematics library
 R is `GNU S' - A language and environment for statistical computing
 and graphics. R is similar to the award-winning S system, which was
 developed at Bell Laboratories by John Chambers et al. It provides a
 wide variety of statistical and graphical techniques (linear and
 nonlinear modelling, statistical tests, time series analysis,
 classification, clustering, ...).
 .
 R is designed as a true computer language with control-flow
 constructions for iteration and alternation, and it allows users to
 add additional functionality by defining new functions. For
 computationally intensive tasks, C, C++ and Fortran code can be
 linked and called at run time.
 .
 This packages provides the libRmath shared and static libraries which can
 be called from standalone C or C++ code.

Package: r-base-html
Architecture: all
Priority: extra
Depends: r-base-core
Replaces: r-base (<= 1.4.1-1), r-recommended (<< 1.9.0)
Suggests: r-doc-html, mozilla | www-browser
Description: GNU R html docs for statistical computing system functions
 R is `GNU S' - A language and environment for statistical computing
 and graphics. R is similar to the award-winning S system, which was
 developed at Bell Laboratories by John Chambers et al. It provides a
 wide variety of statistical and graphical techniques (linear and
 nonlinear modelling, statistical tests, time series analysis,
 classification, clustering, ...).
 .
 R is designed as a true computer language with control-flow
 constructions for iteration and alternation, and it allows users to
 add additional functionality by defining new functions. For
 computationally intensive tasks, C, C++ and Fortran code can be
 linked and called at run time.
 .
 This packages provides html documentation suitable for browsing with a 
 web-browser for the libraries included in the r-base package. It is not 
 a required package as the same documentation is already included for 
 on-line browsing. 

Package: r-base-latex
Architecture: all
Priority: extra
Depends: r-base-core
Replaces: r-base (<= 1.4.1-1), r-recommended (<< 1.9.0)
Description: GNU R LaTeX docs for statistical computing system functions
 R is `GNU S' - A language and environment for statistical computing
 and graphics. R is similar to the award-winning S system, which was
 developed at Bell Laboratories by John Chambers et al. It provides a
 wide variety of statistical and graphical techniques (linear and
 nonlinear modelling, statistical tests, time series analysis,
 classification, clustering, ...).
 .
 R is designed as a true computer language with control-flow
 constructions for iteration and alternation, and it allows users to
 add additional functionality by defining new functions. For
 computationally intensive tasks, C, C++ and Fortran code can be
 linked and called at run time.
 .
 This packages provides latex documentation suitable for off-line printing
 for the libraries included in the r-base package. It is not a required 
 package as the same documentation is already included for on-line browsing.

Package: r-doc-pdf
Architecture: all
Section: doc
Suggests: r-base-core, xpdf-reader | pdf-viewer
Description: GNU R pdf manuals for statistical computing system
 R is `GNU S' - A language and environment for statistical computing
 and graphics. R is similar to the award-winning S system, which was
 developed at Bell Laboratories by John Chambers et al. It provides a
 wide variety of statistical and graphical techniques (linear and
 nonlinear modelling, statistical tests, time series analysis,
 classification, clustering, ...).
 .
 R is designed as a true computer language with control-flow
 constructions for iteration and alternation, and it allows users to
 add additional functionality by defining new functions. For
 computationally intensive tasks, C, C++ and Fortran code can be
 linked and called at run time.
 .
 This packages provides the R manuals in pdf format. The sibling packages
 r-doc-html and r-doc-info provides the same manuals.

Package: r-doc-html
Architecture: all
Section: doc
Suggests: r-base-core, mozilla | www-browser
Replaces: r-base (<= 1.4.1-1)
Description: GNU R html manuals for statistical computing system
 R is `GNU S' - A language and environment for statistical computing
 and graphics. R is similar to the award-winning S system, which was
 developed at Bell Laboratories by John Chambers et al. It provides a
 wide variety of statistical and graphical techniques (linear and
 nonlinear modelling, statistical tests, time series analysis,
 classification, clustering, ...).
 .
 R is designed as a true computer language with control-flow
 constructions for iteration and alternation, and it allows users to
 add additional functionality by defining new functions. For
 computationally intensive tasks, C, C++ and Fortran code can be
 linked and called at run time.
 .
 This packages provides the R manuals in html format. The sibling packages
 r-doc-pdf and r-doc-info provides the same manuals.

Package: r-doc-info
Architecture: all
Section: doc
Replaces: r-base (<= 1.4.1-1)
Suggests: r-base-core, info (>= 3.12) | info-browser
Description: GNU R info manuals statistical computing system
 R is `GNU S' - A language and environment for statistical computing
 and graphics. R is similar to the award-winning S system, which was
 developed at Bell Laboratories by John Chambers et al. It provides a
 wide variety of statistical and graphical techniques (linear and
 nonlinear modelling, statistical tests, time series analysis,
 classification, clustering, ...).
 .
 R is designed as a true computer language with control-flow
 constructions for iteration and alternation, and it allows users to
 add additional functionality by defining new functions. For
 computationally intensive tasks, C, C++ and Fortran code can be
 linked and called at run time.
 .
 This packages provides the R manuals in info format. The sibling packages
 r-doc-html and r-doc-pdf provide the same manuals.

Package: r-recommended
Architecture: all
Depends: r-base-core (>= ${Source-Version}), r-cran-boot (>= 1.2.19), r-cran-cluster (>= 1.9.6-2), r-cran-foreign (>= 0.7-2), r-cran-kernsmooth (>= 2.2.14), r-cran-lattice (>= 0.10.11), r-cran-mgcv (>= 1.1.5), r-cran-nlme (>= 3.1.52), r-cran-rpart (>= 3.1.20), r-cran-survival (>= 2.13.2-1), r-cran-vr (>= 7.2.8)
Description: GNU R collection of recommended packages [metapackage]
 R is `GNU S' - A language and environment for statistical computing
 and graphics. R is similar to the award-winning S system, which was
 developed at Bell Laboratories by John Chambers et al. It provides a
 wide variety of statistical and graphical techniques (linear and
 nonlinear modelling, statistical tests, time series analysis,
 classification, clustering, ...).
 .
 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)
  - VR: The 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.)
  - 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.