Sparse and Dense Matrix Classes and Methods

Douglas Bates <bates@stat.wisc.edu> and Martin Maechler

Classes and methods for dense and sparse matrices and
    operations on them using 'LAPACK' and 'SuiteSparse'.

not possible, since we use data/*.R *and* our classes

The Matrix package includes libraries AMD, CHOLMOD,
COLAMD, CSparse and SPQR from the SuiteSparse collection of Tim
Davis.  All sections of that code are covered by the GPL or
LGPL licenses.  See the directory doc/UFsparse for details.

An Implementation of the Grammar of Graphics

c(
    person("Hadley", "Wickham", role = c("aut", "cre"), email = "h.wickham@gmail.com"),
    person("Winston", "Chang", role = "aut", email = "winston@stdout.org")
    )

An implementation of the grammar of graphics
    in R. It combines the advantages of both base and
    lattice graphics: conditioning and shared axes are
    handled automatically, and you can still build up a
    plot step by step from multiple data sources. It also
    implements a sophisticated multidimensional
    conditioning system and a consistent interface to map
    data to aesthetic attributes. See http://ggplot2.org
    for more information, documentation and examples.

plyr (>= 1.7.1), digest, grid, gtable (>= 0.1.1), reshape2,
scales (>= 0.2.3), proto, MASS

quantreg, Hmisc, mapproj, maps, hexbin, maptools, multcomp,
nlme, testthat, knitr, mgcv

Hadley Wickham [aut, cre],
  Winston Chang [aut]

Stefan Milton Bache <stefan@stefanbache.dk> and
    Hadley Wickham <h.wickham@gmail.com>

Provides a mechanism for chaining commands with a
    new forward-pipe operator, %>%. This operator will forward a
    value, or the result of an expression, into the next function
    call/expression. There is flexible support for the type
    of right-hand side expressions. For more information, see
    package vignette.
    To quote Rene Magritte, "Ceci n'est pas un pipe."

Solving and Optimizing Large-Scale Nonlinear Systems

Barzilai-Borwein spectral methods for solving nonlinear
        system of equations, and for optimizing nonlinear objective
        functions subject to simple constraints. A tutorial style
        introduction to this package is available in a vignette on the
        CRAN download page or, when the package is loaded in an R
        session, with vignette("BB").