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recommended packages. If you also want to build R packages from source,
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also run @code{apt-get install r-base-dev} to obtain the additional
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tools required for this. So-called ``backports'' of the current R
570
packages for the @dfn{stable} distribution of Debian are provided by
571
Johannes Ranke, and available from CRAN. Simply add the line
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deb http://CRAN.R-project.org/bin/linux/debian stable/
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(feel free to use a @CRAN{} mirror instead of the master) to the file
579
@file{/etc/apt/sources.list}, and install as usual. More details on
580
installing and administering R on Debian Linux can be found at
581
@url{http://CRAN.R-project.org/bin/linux/debian/README}. These
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backports should also be suitable for other Debian derivatives. Native
583
backports for Ubuntu are provided by Vincent Goulet and Michael Rutter.
570
packages for at least the @dfn{stable} distribution of Debian are
571
provided by Johannes Ranke, and available from CRAN. See
572
@url{http://CRAN.R-project.org/bin/linux/debian/README} for details on R
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Debian packages and installing the backports, which should also be
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suitable for other Debian derivatives. Native backports for Ubuntu are
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provided by Vincent Goulet and Michael Rutter.
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577
On SUSE, you can set up an installation source for R within Yast by
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(Added in R 2.4.0.)
663
An annotated bibliography (Bib@TeX{} format) of R-related publications
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@url{http://www.R-project.org/doc/bib/R.bib}
670
Books on R by R Core Team members include
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P. Dalgaard (2002), ``Introductory Statistics with R'', Springer: New
675
York, ISBN 0-387-95475-9, @url{http://www.biostat.ku.dk/~pd/ISwR.html}.
677
J. Fox (2002), ``An R and @SPLUS{} Companion to Applied Regression'',
678
Sage Publications, ISBN 0-761-92280-6 (softcover) or 0-761-92279-2
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@url{http://socserv.socsci.mcmaster.ca/jfox/Books/Companion/}.
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J. Maindonald and J. Braun (2003), ``Data Analysis and Graphics Using R:
683
An Example-Based Approach'', Cambridge University Press, ISBN
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0-521-81336-0, @url{http://wwwmaths.anu.edu.au/~johnm/}.
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S. M. Iacus and G. Masarotto (2002), ``Laboratorio di statistica con
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R'', McGraw-Hill, ISBN 88-386-6084-0 (in Italian),@*
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@url{http://www.ateneonline.it/LibroAteneo.asp?item_id=1436}.
673
John M. Chambers (2008), ``Software for Data Analysis: Programming with
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R''. Springer, New York, ISBN 978-0-387-75935-7,
675
@url{http://stat.stanford.edu/~jmc4/Rbook/}.
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Peter Dalgaard (2008), ``Introductory Statistics with R'', 2nd edition.
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Springer, ISBN 978-0-387-79053-4,
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@url{http://www.biostat.ku.dk/~pd/ISwR.html}.
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Robert Gentleman (2008), ``R Programming for Bioinformatics''. Chapman
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& Hall/CRC, Boca Raton, FL, ISBN 978-1-420-06367-7,
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@url{http://www.bioconductor.org/pub/RBioinf/}.
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Stefano M. Iacus (2008), ``Simulation and Inference for Stochastic
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Differential Equations: With R Examples''. Springer, New York, ISBN
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Deepayan Sarkar (2007), ``Lattice: Multivariate Data Visualization with
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R''. Springer, New York, ISBN 978-0-387-75968-5.
692
W. John Braun and Duncan J. Murdoch (2007), ``A First Course in
693
Statistical Programming with R''. Cambridge University Press,
694
Cambridge, ISBN 978-0521872652.
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P. Murrell (2005), ``R Graphics'', Chapman & Hall/CRC, ISBN:
692
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@url{http://www.stat.auckland.ac.nz/~paul/RGraphics/rgraphics.html}.
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W. N. Venables and B. D. Ripley (2002), ``Modern Applied Statistics with
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S'' (4th edition). Springer, ISBN 0-387-95457-0
705
has a home page at @url{http://www.stats.ox.ac.uk/pub/MASS4/} providing
706
additional material. Its companion is
709
W. N. Venables and B. D. Ripley (2000), ``S Programming''. Springer,
714
and provides an in-depth guide to writing software in the S language
715
which forms the basis of both the commercial @SPLUS{} and the Open
716
Source R data analysis software systems. See
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@url{http://www.stats.ox.ac.uk/pub/MASS3/Sprog/} for more information.
719
In addition to material written specifically or explicitly for R,
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documentation for S/@SPLUS{} (see @ref{R and S}) can be used in
721
combination with this @acronym{FAQ} (@pxref{What are the differences
722
between R and S?}). Introductory books include
725
P. Spector (1994), ``An introduction to S and @SPLUS{}'', Duxbury Press.
727
A. Krause and M. Olsen (2005), ``The Basics of @SPLUS{}'' (4th edition).
728
Springer, ISBN 0-387-26109-5.
734
J. C. Pinheiro and D. M. Bates (2000), ``Mixed-Effects Models in S and
735
@SPLUS{}'', Springer, ISBN 0-387-98957-0
739
provides a comprehensive guide to the use of the @strong{nlme} package
740
for linear and nonlinear mixed-effects models.
741
@c This has a home page at @url{http://nlme.stat.wisc.edu/MEMSS/}.
743
As an example of how R can be used in teaching an advanced introductory
744
statistics course, see
747
D. Nolan and T. Speed (2000), ``Stat Labs: Mathematical Statistics
748
Through Applications'', Springer Texts in Statistics, ISBN
753
This integrates theory of statistics with the practice of statistics
754
through a collection of case studies (``labs''), and uses R to analyze
755
the data. More information can be found at
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@url{http://www.stat.Berkeley.EDU/users/statlabs/}.
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William N. Venables and Brian D. Ripley (2002), ``Modern Applied
701
Statistics with S'' (4th edition). Springer, ISBN 0-387-95457-0,
702
@url{http://www.stats.ox.ac.uk/pub/MASS4/}.
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Jose C. Pinheiro and Douglas M. Bates (2000), ``Mixed-Effects Models in
705
S and S-Plus''. Springer, ISBN 0-387-98957-0.
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708
Last, but not least, Ross' and Robert's experience in designing and
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implementing R is described in Ihaka & Gentleman (1996), ``R: A Language
added
removed
doc/manual/R-FAQ.texi
