Taken from Section 5 (Add-On Packages) of the R FAQ (general):
http://cran.r-project.org/doc/FAQ/R-FAQ.html#R-Add_002dOn-Packages


5.1.1 Add-on packages in R

The R distribution comes with the following packages:

base
    Base R functions (and datasets before R 2.0.0).
compiler
    R byte code compiler (added in R 2.13.0).
datasets
    Base R datasets (added in R 2.0.0).
grDevices
    Graphics devices for base and grid graphics (added in R 2.0.0).
graphics
    R functions for base graphics.
grid
    A rewrite of the graphics layout capabilities, plus some support for interaction.
methods
    Formally defined methods and classes for R objects, plus other programming tools, as described in the Green Book.
parallel
    Support for parallel computation, including by forking and by sockets, and random-number generation (added in R 2.14.0).
splines
    Regression spline functions and classes.
stats
    R statistical functions.
stats4
    Statistical functions using S4 classes.
tcltk
    Interface and language bindings to Tcl/Tk GUI elements.
tools
    Tools for package development and administration.
utils
    R utility functions. 

These “base packages” were substantially reorganized in R 1.9.0. The former base was split into the four packages base, graphics, stats, and utils. Packages ctest, eda, modreg, mva, nls, stepfun and ts were merged into stats, package lqs returned to the recommended package MASS, and package mle moved to stats4.

Next: Add-on packages from Omegahat, Previous: Add-on packages in R, Up: Which add-on packages exist for R?
5.1.2 Add-on packages from CRAN

The CRAN src/contrib area contains a wealth of add-on packages, including the following recommended packages which are to be included in all binary distributions of R.

KernSmooth
    Functions for kernel smoothing (and density estimation) corresponding to the book “Kernel Smoothing” by M. P. Wand and M. C. Jones, 1995.
MASS
    Functions and datasets from the main package of Venables and Ripley, “Modern Applied Statistics with S”. (Contained in the VR bundle for R versions prior to 2.10.0.)
Matrix
    A Matrix package. (Recommended for R 2.9.0 or later.)
boot
    Functions and datasets for bootstrapping from the book “Bootstrap Methods and Their Applications” by A. C. Davison and D. V. Hinkley, 1997, Cambridge University Press.
class
    Functions for classification (k-nearest neighbor and LVQ). (Contained in the VR bundle for R versions prior to 2.10.0.)
cluster
    Functions for cluster analysis.
codetools
    Code analysis tools. (Recommended for R 2.5.0 or later.)
foreign
    Functions for reading and writing data stored by statistical software like Minitab, S, SAS, SPSS, Stata, Systat, etc.
lattice
    Lattice graphics, an implementation of Trellis Graphics functions.
mgcv
    Routines for GAMs and other generalized ridge regression problems with multiple smoothing parameter selection by GCV or UBRE.
nlme
    Fit and compare Gaussian linear and nonlinear mixed-effects models.
nnet
    Software for single hidden layer perceptrons (“feed-forward neural networks”), and for multinomial log-linear models. (Contained in the VR bundle for R versions prior to 2.10.0.)
rpart
    Recursive PARTitioning and regression trees.
spatial
    Functions for kriging and point pattern analysis from “Modern Applied Statistics with S” by W. Venables and B. Ripley. (Contained in the VR bundle for R versions prior to 2.10.0.)
survival
    Functions for survival analysis, including penalized likelihood. 

See the CRAN contributed packages page for more information.

Many of these packages are categorized into CRAN Task Views, allowing to browse packages by topic and providing tools to automatically install all packages for special areas of interest.

Some CRAN packages that do not build out of the box on Windows, require additional software, or are shipping third party libraries for Windows cannot be made available on CRAN in form of a Windows binary packages. Nevertheless, some of these packages are available at the “CRAN extras” repository at http://www.stats.ox.ac.uk/pub/RWin/ kindly provided by Brian D. Ripley. Note that this repository is a default repository for recent versions of R for Windows. 

#### Nov. 8, 2011 for R 2.14.0 for Window