R Installation and Administration

Sources, binaries, and documentation for pqR can be obtained from the project webpage at http://pqR-project.org/ or the source code repository at http://github.com/radfordneal/pqR/. The remainder of this section documents how to obtain versions of R produced by the R Core Team.

Sources, binaries and documentation for R can be obtained via CRAN, the “Comprehensive R Archive Network” whose current members are listed at http://cran.r-project.org/mirrors.html.

1.1 Getting and unpacking the sources

The simplest way is to download the most recent R-x.y.z.tar.gz file, and unpack it with

on systems that have a suitable¹ tar installed. On other systems you need to have the gzip program installed, when you can use

The pathname of the directory into which the sources are unpacked should not contain spaces, as most make programs (and specifically GNU make) do not expect spaces.

If you want the build to be usable by a group of users, set umask before unpacking so that the files will be readable by the target group (e.g., umask 022 to be usable by all users). Keep this setting of umask whilst building and installing.

If you use a recent GNU version of tar and do this as a root account (which on Windows includes accounts with administrator privileges) you may see many warnings about changing ownership. In which case you can use

and perhaps also include the option --no-same-permissions. (These options can also be set in the TAR_OPTIONS environment variable: if more than one option is included they should be separated by spaces.)

1.2 Getting patched and development versions

A patched version of the current release, ‘r-patched’, and the current development version, ‘r-devel’, are available as daily tarballs and via access to the R Subversion repository. (For the two weeks prior to the release of a minor (2.x.0) version, ‘r-patched’ tarballs may refer to beta/release candidates of the upcoming release, the patched version of the current release being available via Subversion.)

The tarballs are available from ftp://ftp.stat.math.ethz.ch/pub/Software/R/. Download R-patched.tar.gz or R-devel.tar.gz (or the .tar.bz2 versions) and unpack as described in the previous section. They are built in exactly the same way as distributions of R releases.

1.2.1 Using Subversion and rsync

Sources are also available via https://svn.R-project.org/R/, the R Subversion repository. If you have a Subversion client (see http://subversion.apache.org/), you can check out and update the current ‘r-devel’ from https://svn.r-project.org/R/trunk/ and the current ‘r-patched’ from ‘https://svn.r-project.org/R/branches/R-x-y-branch/’ (where x and y are the major and minor number of the current released version of R). E.g., use

to check out ‘r-devel’ into directory path (which will be created if necessary). The alpha, beta and RC versions of an upcoming x.y.0 release are available from ‘https://svn.r-project.org/R/branches/R-x-y-branch/’ in the four-week period prior to the release.

Note that ‘https:’ is required², and that the SSL certificate for the Subversion server of the R project should be recognized as from a trusted source.

Note that retrieving the sources by e.g. wget -r or svn export from that URL will not work: the Subversion information is needed to build R.

The Subversion repository does not contain the current sources for the recommended packages, which can be obtained by rsync or downloaded from CRAN. To use rsync to install the appropriate sources for the recommended packages, run ./tools/rsync-recommended from the top-level of the R sources.

If downloading manually from CRAN, do ensure that you have the correct versions of the recommended packages: if the number in the file VERSION is ‘x.y.z’ you need to download the contents of ‘http://CRAN.R-project.org/src/contrib/dir’, where dir is ‘x.y.z/Recommended’ for r-devel or x.y-patched/Recommended for r-patched, respectively, to directory src/library/Recommended in the sources you have unpacked. After downloading manually you need to execute tools/link-recommended from the top level of the sources to make the requisite links in src/library/Recommended. A suitable incantation from the top level of the R sources using wget might be (for the correct value of dir)

2 Installing R under Unix-alikes

pqR will configure and build under most common Unix and Unix-alike platforms, in the same way as R-2.15.0, on which pqR is based. Except as noted, the remainder of this section applies equally to R-2.15.0 and pqR.

R-2.15.0 will configure and build on most common Unix and Unix-alike platforms including ‘cpu-*-linux-gnu’ for the ‘alpha’, ‘arm’, ‘hppa’, ‘ix86’, ‘ia64’, ‘m68k’, ‘mips’, ‘mipsel’, ‘powerpc’, ‘s390’, ‘sparc’, and ‘x86_64’ CPUs, ‘i386-apple-darwin’, ‘x86_64-apple-darwin’, ‘i386-sun-solaris’, ‘sparc-sun-solaris’, ‘x86_64-*-freebsd’, and ‘powerpc-ibm-aix6*’ as well as perhaps (it is tested less frequently on these platforms) ‘powerpc-apple-darwin’, ‘i386-*-freebsd’, ‘i386-*-netbsd’ and ‘i386-*-openbsd’.

No binary distributions of pqR are available yet. Versions of R distributed by the R Core Team are available as binary distributions for some common Linux distributions and for OS X (formerly Mac OS). See the FAQ for current details. These are installed in platform-specific ways, so for the rest of this chapter we consider only building from the sources.

2.1 Simple compilation

First review the essential and useful tools and libraries in Essential and useful other programs under a Unix-alike, and install those you want or need. Ensure that the environment variable TMPDIR is either unset (and /tmp exists and can be written in and scripts can be executed from) or points to a valid temporary directory (one from which execution of scripts is allowed).

Choose a place to install the R tree (R is not just a binary, but has additional data sets, help files, font metrics etc). Let us call this place R_HOME. Untar the source code. This should create directories src, doc, and several more under a top-level directory: change to that top-level directory. Issue the following commands:

(See Using make if your make is not called ‘make’.) Users of Debian-based 64-bit systems³ may need

Once make has finished, you should check that the built system works correctly by

Failures are not necessarily problems as they might be caused by missing functionality,⁴ but you should look carefully at any reported discrepancies. (Some non-fatal errors are expected in locales that do not support Latin-1, in particular in true C locales and non-UTF-8 non-Western-European locales.) A failure in tests/ok-errors.R may indicate inadequate resource limits (see Running R).

Note: Setting the R_MATPROD_TEST_COUNT environment variable to a value greater than the default of 200 will increase the number of random cases of matrix multiplication that are generated and checked for correctness. Setting R_MATPROD_TEST_BLAS to TRUE will case the BLAS matrix multiplication routines to be tested as well as the C matprod functions.

If the command configure and make commands execute successfully, a shell-script front-end called R will be created and copied to R_HOME/bin. You can copy this script to a place where users can invoke it, for example to /usr/local/bin/R. You could also copy the man page R.1 to a place where your man reader finds it, such as /usr/local/man/man1. If you want to install the complete R tree to, e.g., /usr/local/lib/R, see Installation. Note: you do not need to install R: you can run it from where it was built.

You do not necessarily have to build R in the top-level source directory (say, TOP_SRCDIR). To build in BUILDDIR, run

and so on, as described further below. This has the advantage of always keeping your source tree clean and is particularly recommended when you work with a version of R from Subversion. (You may need GNU make to allow this, and you will need no spaces in the path to the build directory.)

Now rehash if necessary, type R, and read the R manuals and the R FAQ (files FAQ or doc/manual/R-FAQ.html, or http://CRAN.R-project.org/doc/FAQ/R-FAQ.html which always has the version for the latest release of R).

Most of the files in the source directory are human-created, but a few are created automatically from other files. One example is NEWS, supplied with the source directory, but also re-created from doc/NEWS.Rd, as part of the normal build process. Other such files do not normally need to be re-created. In particular, you will not usually need to re-create configure, which is derived from configure.ac, VERSION, and the macro definitions in the m4 directory. If you do want to re-create this or other other automatically built files (such as src/main/gramRd.c from src/main/gramRd.y), you will need to run ./configure with the --enable-maintainer-mode option, which creates a Makefile with the appropriate rules. Note that these files are always recreated in the source directory, even if you are using a separate build directory. (When re-creating configure, you should not use a separate build directory, since this has the effect of stripping comments from configure.)

There is a possible logical flaw with the concept of re-creating configure using a Makefile that can be created only if you have a working configure script — if necessary, you can re-create configure as follows, when in the main source directory:

These commands are in the create-configure shell file in the main directory of a pqR source distribution.

2.2 Help options

By default HTML help pages are created when needed rather than being built at install time.

If you need to disable the server and want HTML help, there is the option to build HTML pages when packages are installed (including those installed with R). This is enabled by the configure option --enable-prebuilt-html. Whether R CMD INSTALL (and hence install.packages) pre-builds HTML pages is determined by looking at the R installation and is reported by R CMD INSTALL --help: it can be overridden by specifying one of the INSTALL options --html or --no-html.

The server is disabled by setting the environment variable R_DISABLE_HTTPD to a non-empty value, either before R is started or within the R session before HTML help (including help.start) is used. It is also possible that system security measures will prevent the server from being started, for example if the loopback interface has been disabled. See ?tools::startDynamicHelp for more details.

2.3 Making the manuals

You will not be able to build any of these unless you have makeinfo version 4.7 or later installed, and for PDF you must have texi2dvi and texinfo.tex installed (which are part of the GNU texinfo distribution but are, especially texinfo.tex, often made part of the TeX package in re-distributions).

The PDF versions can be viewed using any recent PDF viewer: they have hyperlinks that can be followed. The info files are suitable for reading online with Emacs or the standalone GNU info program. The PDF versions will be created using the paper size selected at configuration (default ISO a4): this can be overridden by setting R_PAPERSIZE on the make command line, or setting R_PAPERSIZE in the environment and using make -e. (If re-making the manuals for a different paper size, you should first delete the file doc/manual/version.texi.)

There are some issues with making the PDF reference manual, refman.pdf. The help files contain both ISO Latin1 characters (e.g. in text.Rd) and upright quotes, neither of which are contained in the standard LaTeX Computer Modern fonts. We have provided four alternatives:

The default can be overridden by setting the environment variable R_RD4PDF. (On Unix-alikes, this will be picked up at install time and stored in etc/Renviron, but can still be overridden when the manuals are built.) The default value for R_RD4PDF is ‘times,inconsolata,hyper’: omit ‘hyper’ if you do not want hyperlinks (e.g. for printing the manual) or do not have LaTeX package hyperref, and omit ‘inconsolata’ if you do not have LaTeX package inconsolata installed.

2.4 Installation

To ensure that the installed tree is usable by the right group of users, set umask appropriately (perhaps to ‘022’) before unpacking the sources and throughout the build process.

(or, when building outside the source, TOP_SRCDIR/configure, etc) have been completed successfully, you can install the complete R tree to your system by typing

where prefix is determined during configuration (typically /usr/local) and can be set by running configure with the option --prefix, as in

This causes make install to install the R script to /where/you/want/R/to/go/bin, and so on. The prefix of the installation directories can be seen in the status message that is displayed at the end of configure. You can install into another directory tree by using

at least with GNU make (and current Solaris and FreeBSD make, but not some older Unix makes).

More precise control is available at configure time via options: see configure --help for details. (However, most of the ‘Fine tuning of the installation directories’ options are not used by R.)

Configure options --bindir and --mandir are supported and govern where a copy of the R script and the man page are installed.

The configure option --libdir controls where the main R files are installed: the default is ‘eprefix/LIBnn’, where eprefix is the prefix used for installing architecture-dependent files, defaults to prefix, and can be set via the configure option --exec-prefix.

Each of bindir, mandir and libdir can also be specified on the make install command line (at least for GNU make).

The configure or make variables rdocdir and rsharedir can be used to install the system-independent doc and share directories to somewhere other than libdir. The C header files can be installed to the value of rincludedir: note that as the headers are not installed into a subdirectory you probably want something like rincludedir=/usr/local/include/R-2.15.0.

If you want the R home to be something other than libdir/R, use rhome: for example

If you have made R as a shared/dynamic library you can install it in your system’s library directory by

will install stripped executables, and on platforms where this is supported, stripped libraries in directories lib and modules and in the standard packages.

Note that installing R into a directory whose path contains spaces is not supported, and at least some aspects (such as installing source packages) will not work.

Once again, it is optional to specify prefix, libdir or rhome (the PDF manuals are installed under the R home directory). (make install-info needs Perl installed if there is no command install-info on the system.)

More precise control is possible. For info, the setting used is that of infodir (default prefix/info, set by configure option --infodir). The PDF files are installed into the R doc tree, set by the make variable rdocdir.

A staged installation is possible, that it is installing R into a temporary directory in order to move the installed tree to its final destination. In this case prefix (and so on) should reflect the final destination, and DESTDIR should be used: see http://www.gnu.org/prep/standards/html_node/DESTDIR.html.

You can optionally install the run-time tests that are part of make check-all by

2.5 Uninstallation

optionally specifying prefix etc in the same way as specified for installation.

This will also uninstall any installed manuals. There are specific targets to uninstall info and PDF manuals in file doc/manual/Makefile.

Target uninstall-tests will uninstall any installed tests, as well as removing the directory tests containing the test results.

2.6 Sub-architectures

Some platforms can support closely related builds of R which can share all but the executables and dynamic objects. Examples include builds under Solaris for different chips (in particular, 32- and 64-bit builds), 64- and 32- bit builds on ‘x86_64’ Linux and different CPUs (e.g. ‘ppc’, ‘i386’ and ‘x86_64’) under (Mac) OS X >= 10.4.

R supports the idea of architecture-specific builds, specified by adding ‘r_arch=name’ to the configure line. Here name can be anything non-empty, and is used to name subdirectories of lib, etc, include and the package libs subdirectories. Example names from other systems are the use of sparcv9 on Sparc Solaris and 32 by gcc on ‘x86_64’ Linux.

If you have two or more such builds you can install them over each other (and for 32/64-bit builds on one architecture, one build can be done without ‘r_arch’). The space savings can be considerable: on ‘x86_64’ Linux a basic install (without debugging symbols) took 63Mb, and adding a 32-bit build added 6Mb. If you have installed multiple builds you can select which build to run by

R CMD INSTALL will detect if more than one build is installed and try to install packages with the appropriate library objects for each. This will not be done if the package has an executable configure script or a src/Makefile file. In such cases you can install for extra builds by

If you want to mix sub-architectures compiled on different platforms (for example ‘x86_64’ Linux and ‘i686’ Linux), it is wise to use explicit names for each, and you may also need to set libdir to ensure that they install into the same place.

When sub-architectures are used the version of Rscript in e.g. /usr/bin will be the last installed, but architecture-specific versions will be available in e.g. /usr/lib64/R/bin/exec${R_ARCH}. Normally all installed architectures will run on the platform so the architecture of Rscript itself does not matter. The executable Rscript will run the R script, and at that time the setting of the R_ARCH environment variable determines the architecture which is run.

Sub-architectures are also used on Windows, but by selecting executables within the appropriate bin directory, R_HOME/bin/i386 or R_HOME/bin/x64. For backwards compatibility with R < 2.12.0, there are executables R_HOME/bin/R.exe or R_HOME/bin/Rscript.exe: these will run an executable from one of the subdirectories, which one being taken first from the R_ARCH environment variable, then from the --arch command-line option⁶ and finally from the installation default (which is 32-bit for a combined 32/64 bit R installation).

2.6.1 Multilib

On Linux⁷, there is an alternative mechanism for mixing 32-bit and 64-bit libraries known as multilib. If a Linux distribution supports multilib, then parallel builds of R may be installed in the sub-directories lib (32-bit) and lib64 (64-bit). The build to be run may then be chosen using the setarch command. For example, a 32-bit build may be chosen by

The setarch command is only operational if both 32-bit and 64-bit builds are installed. If there is only one installation of R, then this will always be run regardless of the architecture specified by the setarch command.

There can be problems with installing packages on the non-native architecture. It is a good idea to run e.g. setarch i686 R for sessions in which packages are to be installed, even if that is the only version of R installed (since this tells the package installation code the architecture needed).

At present there is a potential problem with packages using Java, as the post-install for a ‘i386’ RPM on ‘x86_64’ Linux reconfigures Java and will find the ‘x86_64’ Java. If you know where a 32-bit Java is installed you may be able to run (as root)

When this mechanism is used, the version of Rscript in e.g. /usr/bin will be the last installed, but an architecture-specific version will be available in e.g. /usr/lib64/R/bin. Normally all installed architectures will run on the platform so the architecture of Rscript does not matter.

2.7 Other Options

Other configuration options for can be listed with

configure
--help

. For pqR, these include options for enabling or disabling use of helper threads and compressed pointers, which are discussed in Configuration on a Unix-alike.

Most options not listed elsewhere in this manual are either standard autoconf options not relevant to R or are intended for specialist uses by the R developers.

2.8 Stack growth direction

The direction of growth for the C stack is assumed by default to be downwards, as is the case for almost all current platforms. To override this, the C pre-processor symbol R_CStackDir can be defined to be -1, which can usually be done by including an argument of R_CStackDir=-1 in the CFLAGS variable.

2.9 Testing a Unik-alike Installation

If this has been done, two testing routes are available. The first is to move to the home directory of the R installation (as given by R.home()) and run

and other useful targets are test-BasePackages and test-Recommended to the run tests of the standard and recommended packages (if installed) respectively.

This re-runs all the tests relevant to the installed R (including for example code in the package vignettes), but not for example the ones checking the example code in the manuals nor making the standalone Rmath library. This can occasionally be useful when the operating environment has been changed, for example by OS updates or by substituting the BLAS (see Shared BLAS).

runs the basic tests and then all the tests on the standard and recommended packages. These tests can be run from anywhere: the basic tests write their results in the tests folder of the R home directory and run slightly fewer tests than the first approach: in particular they do not test Internet access.

These tests work best if diff (in Rtools*.exe for Windows users) is in the path, and on some systems need the collation locale set manually (the R code tries to do so but it may not be possible to reset it): so if needed try setting the environment variable LC_COLLATE to ‘C’ before starting R.

It is possible to test the installed packages (but not the package-specific tests) by testInstalledPackages even if make install-tests was not run.

Note that the results may depend on the language set for times and messages: for maximal similarity to reference results you may want to try setting

3 Installing R under Windows

Recent versions of pqR have been sucessfully installed under Windows 7, 8, 8.1, and 10. The src/gnuwin32/INSTALL file contains instructions for how to do this. This section describes installation of R-2.15.0, but may also be relevant to pqR.

The bin/windows directory of a CRAN site contains binaries for a base distribution and a large number of add-on packages from CRAN to run on Windows XP or later on ix86 CPUs (including AMD64/Intel64⁸ chips and Windows x64).

Your file system must allow long file names (as is likely except perhaps for some network-mounted systems).

Installation is via the installer R-2.15.1-win.exe. Just double-click on the icon and follow the instructions. When installing on a 64-bit version of Windows the options will include 32- or 64-bit versions of R (and the default is to install both). You can uninstall R from the Control Panel.

Note that you will be asked to choose a language for installation, and that choice applies to both installation and un-installation but not to running R itself.

3.1 Building from source

Step-by-step directions for installing pqR on Windows are in src/gnuwin32/INSTALL. The instructions below also generally apply to pqR as well as to R Core versions.

R can be built as either a 32-bit or 64-bit application on Windows: to build the 64-bit application you need a 64-bit edition of Windows: such an OS can also be used to build 32-bit R.

The standard installer combines 32-bit and 64-bit builds into a single executable which can then be installed into the same location and share all the files except the .exe and .dll files and some configuration files in the etc directory.

3.1.1 Getting the tools

The Rtools*.exe executable installer described in The Windows toolset also includes some source files in addition to the R source as noted below. You should run it first, to obtain a working tar and other necessities.

The installer has the option of adding extra files to the source directory, but this is not advised, since file ownership problems can arise. It is better to add them (plus files needed for cairo) by untarring a win-extras file obtained from pqR-project.org, as described in src/gnuwin32/INSTALL.

Note that the name of the intended source directory, e.g. pqR-YYYY-MM-DD, should not contain spaces. We will call this directory R_HOME below.

The toolchain used as from R 2.14.2 differs from from that used for R 2.12.0 to R 2.14.1.

3.1.2 Getting the source files

The following additional items are normally installed by Rtools215.exe. If instead you choose to do a completely manual build you will also need

3.1.3 Building the core files

Set the environment variable TMPDIR to point to a writable directory, with a path specified with forward slashes and no spaces. (The default is /tmp, which may not be useful on Windows.)

You may need to compile under a case-honouring file system: we found that a samba-mounted file system (which maps all file names to lower case) did not work.

Open a command window at R_HOME/src/gnuwin32. Copy one of the files MkRules.dist32, MkRules.dist32-sse2, or MkRules.dist64 to MkRules.local and edit the settings there. Then run

3.1.4 Building the bitmap files

The file R_HOME/library/grDevices/libs/{i386,x64}Rbitmap.dll is not built automatically.

Running make in R_HOME/src/gnuwin32/bitmap or make bitmapdll in R_HOME/src/gnuwin32 should build Rbitmap.dll and install it under R_HOME/library/grDevices/libs.

3.1.5 Building the cairo devices

The devices based on cairographics (svg, cairo_pdf, cairo_ps and the type = "cairo" versions of png, jpeg, tiff and bmp) are implemented in a separate DLL winCairo.dll which is loaded when one of these devices is first used. It is not built by default, and needs to be built after Rbitmap.dll, by make cairodevices.

To enable the building of these devices you need to install the static cairographics libraries built by Simon Urbanek at http://www.rforge.net/Cairo/files/cairo-current-win.tar.gz. Set the macro ‘CAIRO_HOME’ in MkRules.local. (Note that this tarball unpacks with a top-level directory src/: ‘CAIRO_HOME’ needs to include that directory in its path.) These files are also included in the win-extras tarball that you can obtain from pqR-project.org, as described in src/gnuwin32/INSTALL.

3.1.6 Checking the build

3.1.7 Building the manuals

See the Making the manuals section in the Unix-alike section for setting options such as the paper size and the fonts used.

3.1.8 Building the Inno Setup installer

You need to have the files for a complete R build, including bitmap and Tcl/Tk support and the manuals, as well as the recommended packages and Inno Setup (see The Inno Setup installer).

will make all the pieces and the installers and put them in the gnuwin32/cran subdirectory, then check the build. This works by building all the parts in the sequence:

The parts can be made individually if a full build is not needed, but earlier parts must be built before later ones. (The Makefile doesn’t enforce this dependency—some build targets force a lot of computation even if all files are up to date.) The first four targets are the default build if just make (or make all) is run.

If you want to customize the installation by adding extra packages, replace make rinstaller by something like

An alternative way to customize the installer starting with a binary distribution is to first make an installation of R from the standard installer, then add packages and make other customizations to that installation. Then (after having customized file MkRules, possibly via MkRules.local, and having made R in the source tree) in src/gnuwin32/installer run

where rootdir is the path to the root of the customized installation (in double quotes if it contains spaces or backslashes).

Both methods create an executable with a standard name such as R-2.15.1-win.exe, so please rename it to indicate that it is customized. If you intend to distribute a customized installer please do check that license requirements are met – note that the installer will state that the contents are distributed under GPL-2 and this has a requirement for you to supply the complete sources (including the R sources even if you started with a binary distribution of R, and also the sources of any extra packages (including their external software) which are included).

will create an installer that defaults to installing R to run in SDI mode. See src/gnuwin32/installer/Makefile for the names and values that can be set.

The standard CRAN distribution of a 32/64-bit installer is made by first building 32-bit R (just

is needed), and then building 64-bit R with the macro HOME32 set in file MkRules.local to the top-level directory of the 32-bit build. Then the make rinstaller step copies the files that differ between architectures from the 32-bit build as it builds the installer image.

3.1.9 Building the MSI installer

It is also possible to build an installer for use with Microsoft Installer. This is intended for use by sysadmins doing automated installs, and is not recommended for casual use.

It makes use of the Windows Installer XML (WiX) toolkit version 3.0 or 3.5 available from http://wix.sourceforge.net/. Once WiX is installed, set the path to its home directory in MkRules.local.

You need to have the files for a complete R build, including bitmap and Tcl/Tk support and the manuals, as well as the recommended packages. There is no option in the installer to customize startup options, so edit etc/Rconsole and etc/Rprofile.site to set these as required. Then

which will result in a file with a name like R-2.15.1-win32.msi. This can be double-clicked to be installed, but those who need it will know what to do with it (usually by running msiexec /i with additional options). Properties that users might want to set from the msiexec command line include ‘ALLUSERS’, ‘INSTALLDIR’ (something like c:\Program Files\R\R-2.15.1) and ‘RMENU’ (the path to the ‘R’ folder on the start menu) and ‘STARTDIR’ (the starting directory for R shortcuts, defaulting to something like c:\Users\name\Documents\R).

The MSI installer can be built both from a 32-bit build of R (R-2.15.1-win32.msi) and from a 64-bit build of R (R-2.15.1-win64.msi, optionally including 32-bit files by setting the macro HOME32, when the name is R-2.15.1-win.msi). Unlike the main installer, a 64-bit MSI installer can only be run on 64-bit Windows.

Thanks to David del Campo (Dept of Statistics, University of Oxford) for suggesting WiX and building a prototype installer.

3.1.10 Cross-building on Linux

3.1.11 64-bit Windows builds

To build a 64-bit version of R you need a 64-bit toolchain: the only one discussed here is based on the work of the MinGW-w64 project (http://sourceforge.net/projects/mingw-w64/, but commercial compilers such as those from Intel and PGI could be used (and have been by R redistributors).

Support for MinGW-w64 was developed in the R sources over the period 2008–10 and was first released as part of R 2.11.0. The assistance of Yu Gong at a crucial step in porting R to MinGW-w64 is gratefully acknowledged, as well as help from Kai Tietz, the lead developer of the MinGW-w64 project.

Windows 64-bit is now completely integrated into the R and package build systems.

3.2 Testing an Installation

The Rtools are not needed to run these tests. but more comprehensive analysis of errors will be given if diff is in the path (and errorsAreFatal = FALSE is then not needed below).

runs the basic tests and then all the tests on the standard and recommended packages. These tests can be run from anywhere: they write their results in the tests folder of the R home directory (as given by R.home()), and hence may need to be run under the account used to install R.

4 Installing R under (Mac) OS X

The current version of pqR has tested under OS X, and works with the Xcode compilers (except that these do not support OpenMP, and hence do not support helper threas), and with recent versions of gcc (4.7 to 4.9). This section describes R-2.15.0, but may apply to pqR as well.

The bin/macosx directory of a CRAN site contains binaries for OS X for a base distribution and a large number of add-on packages from CRAN to run on OS X 10.[567].

The simplest way is to use R-2.15.0.pkg: just double-click on the icon. Note that Tcl/Tk and the compilers need to be installed separately if needed.

4.1 Building from source on (Mac) OS X

If you want to build this port from the sources, you should read the R for Mac OS X FAQ for full details. You will need to collect and install some tools as explained in that document. Then you have to unpack the R sources and configure R appropriately, for example

and then sit back and wait. The first option enables use of a BLAS built into OS X. This may be much faster that the BLAS distributed with pqR, especially if you have many processor cores, but not necessarily. The accuracy of results may also differ.

The second line of options are also default on OS X, but needed only if you want to build R for use with R.app Console, and imply --enable-R-shlib to build R as a shared/dynamic library. These options configure R to be built and installed as a framework called R.framework. The default installation path for R.framework is /Library/Frameworks but this can be changed at configure time by specifying the flag --enable-R-framework[=DIR] or at install time as

For compatibility with the CRAN distribution you may need to specify --with-included-gettext to avoid linking against a ‘libintl’ dynamic library you may have available, for example in /usr/local/lib.

Note that building the R.app GUI console is a separate project: see the OS X FAQ for details.

5 Running R

How to start R and what command-line options are available is discussed in Invoking R in An Introduction to R.

You should ensure that the shell has set adequate resource limits: R expects a stack size of at least 8MB and to be able to open at least 256 file descriptors. (Any modern OS will have default limits at least as large as these, but apparently NetBSD does not. Use the shell command ulimit (sh/bash) or limit (csh/tcsh) to check.)

R makes use of a number of environment variables, the default values of many of which are set in file R_HOME/etc/Renviron (there are none set by default on Windows and hence no such file). These are set at configure time, and you would not normally want to change them – a possible exception is R_PAPERSIZE (see Setting paper size). The paper size will be deduced from the ‘LC_PAPER’ locale category if it exists and R_PAPERSIZE is unset, and this will normally produce the right choice from ‘a4’ and ‘letter’ on modern Unix-alikes (but can always be overridden by setting R_PAPERSIZE).

Various environment variables can be set to determine where R creates its per-session temporary directory. The environment variables TMPDIR, TMP and TEMP are searched in turn and the first one which is set and points to a writable area is used. If none do, the final default is /tmp on Unix-alikes and the value of R_USER on Windows.

Some Unix-alike systems are set up to remove files and directories periodically from /tmp, for example by a cron job running tmpwatch. Set TMPDIR to another directory before running long-running jobs on such a system.

Note that TMPDIR will be used to execute configure scripts when installing packages, so if /tmp has been mounted as ‘noexec’, TMPDIR needs to be set to a directory from which execution is allowed.

6 Add-on packages

It is helpful to use the correct terminology. A package is loaded from a library by the function library(). Thus a library is a directory containing installed packages; the main library is R_HOME/library, but others can be used, for example by setting the environment variable R_LIBS or using the R function .libPaths().

6.1 Default packages

(plus, of course, base) and this can be changed by setting the option in startup code (e.g. in ~/.Rprofile). It is initially set to the value of the environment variable R_DEFAULT_PACKAGES if set (as a comma-separated list). Setting R_DEFAULT_PACKAGES=NULL ensures that only package base is loaded.

Changing the set of default packages is normally used to reduce the set for speed when scripting: in particular not using methods will reduce the start-up time by a factor of up to two (and this is done by Rscript). But it can also be used to customize R, e.g. for class use.

6.2 Managing libraries

R packages are installed into libraries, which are directories in the file system containing a subdirectory for each package installed there.

R comes with a single library, R_HOME/library which is the value of the R object ‘.Library’ containing the standard and recommended⁹ packages. Both sites and users can create others and make use of them (or not) in an R session. At the lowest level ‘.libPaths()’ can be used to add paths to the collection of libraries or to report the current collection.

R will automatically make use of a site-specific library R_HOME/site-library if this exists (it does not in a vanilla R installation). This location can be overridden by setting¹⁰ ‘.Library.site’ in R_HOME/etc/Rprofile.site, or (not recommended) by setting the environment variable R_LIBS_SITE. Like ‘.Library’, the site libraries are always included by ‘.libPaths()’.

Users can have one or more libraries, normally specified by the environment variable R_LIBS_USER. This has a default value (use ‘Sys.getenv("R_LIBS_USER")’ within an R session to see what it is), but only is used if the corresponding directory actually exists (which by default it will not).

Both R_LIBS_USER and R_LIBS_SITE can specify multiple library paths, separated by colons (semicolons on Windows).

6.3 Installing packages

Packages may be distributed in source form or compiled binary form. Installing source packages which contain C/C++/Fortran code requires that compilers and related tools be installed. Binary packages are platform-specific and generally need no special tools to install, but see the documentation for your platform for details.

Note that you may need to specify implicitly or explicitly the library to which the package is to be installed. This is only an issue if you have more than one library, of course.

If installing packages on a Unix-alike to be used by other users, ensure that the system umask is set to give sufficient permissions (see also Sys.umask in R). (To a large extent this is unnecessary in recent versions of R, which install packages as if umask = 022.)

For most users it suffices to call ‘install.packages(pkgname)’ or its GUI equivalent if the intention is to install a CRAN package and internet access is available.¹¹ On most systems ‘install.packages()’ will allow packages to be selected from a list box.

The part ‘-l /path/to/library’ can be omitted, in which case the first library of a normal R session is used (that shown by .libPaths()[1]).

Ensure that the environment variable TMPDIR is either unset (and /tmp exists and can be written in and executed from) or points to a valid temporary directory.

There are a number of options available: use R CMD INSTALL --help to see the current list.

Alternatively, packages can be downloaded and installed from within R. First set the option CRAN to your nearest CRAN mirror using chooseCRANmirror(). Then download and install packages pkg1 and pkg2 by

The essential dependencies of the specified packages will also be fetched. Unless the library is specified (argument lib) the first library in the library search path is used: if this is not writable, R will ask the user (in an interactive session) if the default user library should be created, and if allowed to will install the packages there.

If you want to fetch a package and all those it depends on (in any way) that are not already installed, use e.g.

install.packages can install a source package from a local .tar.gz file by setting argument repos to NULL: this will be selected automatically if the name given is a single .tar.gz file.

install.packages can look in several repositories, specified as a character vector by the argument repos: these can include a CRAN mirror, Bioconductor, Omegahat, R-forge, local archives, local files, …). Function setRepositories() can select amongst those repositories that the R installation is aware of.

Naive users sometimes forget that as well as installing a package, they have to use library to make its functionality available.

6.3.1 Windows

What install.packages does by default is different on Unix-alikes (except OS X) and Windows. On Unix-alikes it consults the list of available source packages on CRAN (or other repository/ies), downloads the latest version of the package sources, and installs them (via R CMD INSTALL). On Windows it looks (by default) at the list of binary versions of packages available for your version of R and downloads the latest versions (if any), although optionally it will also download and install a source package by setting the type argument.

On Windows install.packages can also install a binary package from a local zip file by setting argument repos to NULL. Rgui.exe has a menu Packages with a GUI interface to install.packages, update.packages and library.

Windows binary packages for R are nowadays distributed as a single binary containing either or both architectures.

R CMD INSTALL works in Windows to install source packages if you have set up the tools needed (see The Windows toolset). No additional tools are needed if the package does not contain compiled code, and install.packages(type="source") will work for such packages (and for those with compiled code if the tools are in the path).

We have seen occasional permission problems after unpacking source packages on some Vista/Windows 7/Server 2008 systems: these have been circumvented by setting the environment variable R_INSTALL_TAR to ‘tar.exe’.

If you have only a source package that is known to work with current R and just want a binary Windows build of it, you could make use of the building service offered at http://win-builder.r-project.org/.

For almost all packages R CMD INSTALL will attempt to install both 32- and 64-bit builds of a package if run from a 32/64-bit install of R on a 64-bit version of Windows. It will report success if the installation of the architecture of the running R succeeded, whether or not the other architecture was successfully installed.

The exceptions are packages with a non-empty configure.win script or which make use of src/Makefile.win. If configure.win does something appropriate to both architectures use¹² option --force-biarch: otherwise

R CMD INSTALL
--merge-multiarch

can be applied to a source tarball to merge separate 32- and 64-bit installs. (This can only be applied to a tarball, and will only succeed if both installs succeed.)

If you have a package without compiled code and no Windows-specific help, you can zip up an installation on another OS and install from the that zip file on Windows. However, such a package can be installed from the sources on Windows without any additional tools.

6.3.2 OS X

On OS X install.packages works as it does on other Unix-alike systems, but there are additional types mac.binary* (the default in the CRAN distribution) that can be passed to install.packages in order to download and install binary packages from a suitable repository, and type mac.binary.leopard is the default for CRAN builds of R. These OS X binary package files have the extension ‘tgz’. The R.app GUI provides for installation of either binary or source packages, from CRAN or local files.

6.3.3 Customizing package compilation

The R system and package-specific compilation flags can be overridden or added to by setting the appropriate Make variables in the personal file HOME/.R/Makevars-R_PLATFORM (but HOME/.R/Makevars.win or HOME/.R/Makevars.win64 on Windows), or if that does not exist, HOME/.R/Makevars, where ‘R_PLATFORM’ is the platform for which R was built, as available in the platform component of the R variable R.version.

Package developers are encouraged to use this mechanism to enable a reasonable amount of diagnostic messaging (“warnings”) when compiling, such as e.g. -Wall -pedantic for tools from GCC, the Gnu Compiler Collection.

Note that this mechanism can also be used when it necessary to change the optimization level for a particular package. For example

There is also provision for a site-wide Makevars.site file under R_HOME/etc (in a sub-architecture-specific directory if appropriate). This is read immediately after Makeconf.

6.3.4 Multiple sub-architectures

When installing packages from their sources, there are some extra considerations on installations which use sub-architectures. These are commonly used on (Mac) OS X and Windows, but can in principle be used on other platforms.

When a source package is installed by a build of R which supports multiple sub-architectures, the normal installation process installs the packages for all sub-architectures, but only tests it can be loaded under the current sub-architecture. The exceptions are

In those cases only the current architecture is installed. Further sub-architectures can be installed by

using the path to R or R --arch to select the additional sub-architecture. On Windows there is also

R CMD
INSTALL --merge-multiarch

to build and merge the two architectures, starting with a source tarball.

6.3.5 Byte-compilation

Byte compilation is not recommended in pqR, and can only be enabled by very deliberate measures, as described in help(compile) from the compiler package.

6.4 Updating packages

The command update.packages() is the simplest way to ensure that all the packages on your system are up to date. Set the repos argument as in the previous section. The update.packages() downloads the list of available packages and their current versions, compares it with those installed and offers to fetch and install any that have later versions on the repositories.

An alternative interface to keeping packages up-to-date is provided by the command packageStatus(), which returns an object with information on all installed packages and packages available at multiple repositories. The print and summary methods give an overview of installed and available packages, the upgrade method offers to fetch and install the latest versions of outdated packages.

One sometimes-useful additional piece of information that packageStatus() returns is the status of a package, as "ok", "upgrade" or "unavailable" (in the currently selected repositories). For example

6.5 Removing packages

Packages can be removed in a number of ways. From a command prompt they can be removed by

Finally, in most installations one can just remove the package directory from the library.

6.6 Setting up a package repository

Utilities such as install.packages can be pointed at any CRAN-style repository, and R users may want to set up their own. The ‘base’ of a repository is a URL such as http://www.omegahat.org/R/: this must be an URL scheme that download.packages supports (which also includes ‘ftp://’ and ‘file://’, but not on most systems ‘https://’). Under that base URL there should be directory trees for one or more of the following types of package distributions:

Each terminal directory must also contain a PACKAGES file. This can be a concatenation of the DESCRIPTION files of the packages separated by blank lines, but only a few of the fields are needed. The simplest way to set up such a file is to use function write_PACKAGES in the tools package, and its help explains which fields are needed. Optionally there can also be a PACKAGES.gz file, a gzip-compressed version of PACKAGES—as this will be downloaded in preference to PACKAGES it should be included for large repositories. (If you have a mis-configured server that does not report correctly non-existent files you will need PACKAGES.gz.)

To add your repository to the list offered by setRepositories(), see the help file for that function.

A repository can contain subdirectories, when the descriptions in the PACKAGES file of packages in subdirectories must include a line of the form

6.7 Checking installed source packages

It can be convenient to run R CMD check on an installed package, particularly on a platform which uses sub-architectures. The outline of how to do this is, with the source package in directory pkgname (or a tarball filename):

Where sub-architectures are in use the R CMD check line can be repeated with additional architectures by

where --extra-arch selects only those checks which depend on the installed code and not those which analyse the sources. (If multiple sub-architectures fail only because they need different settings, e.g. environment variables, --no-multiarch may need to be added to the INSTALL lines.) On (Mac) OS X and other Unix-alikes the architecture to run is selected by --arch: this can also be used on Windows with R_HOME/bin/R.exe, but it is more usual to select the path to the Rcmd.exe of the desired architecture.

So on Windows to install, check and package for distribution a source package from a tarball which has been tested on another platform one might use

where one might want to run the second and third lines in a different shell with different settings for environment variables and the path (to find external software, notably for Gtk+).

R CMD INSTALL can do a i386 install and then add the x64 DLL from a single command by

7 Internationalization and Localization

Internationalization refers to the process of enabling support for many human languages, and localization to adapting to a specific country and language.

Historically R worked in the ISO Latin-1 8-bit character set and so covered English and most Western European languages (if not necessarily their currency symbols). Since R 2.1.0 it has supported multi-byte character sets such as UTF-8 and others used for Chinese, Japanese and Korean.

Current builds of R support all the character sets that the underlying OS can handle. These are interpreted according to the current locale, a sufficiently complicated topic to merit a separate section. Note though that R has no built-in support for right-to-left languages and bidirectional output, relying on the OS services. For example, how character vectors in UTF-8 containing both English digits and Hebrew characters are printed is OS-dependent (and perhaps locale-dependent).

The other aspect of the internationalization is support for the translation of messages. This is enabled in almost all builds of R.

7.1 Locales

A locale is a description of the local environment of the user, including the preferred language, the encoding of characters, the currency used and its conventions, and so on. Aspects of the locale are accessed by the R functions Sys.getlocale and Sys.localeconv.

The system of naming locales is OS-specific. There is quite wide agreement on schemes, but not on the details of their implementation. A locale needs to specify

R is principally concerned with the first (for translations) and third. Note that the charset may be deducible from the language, as some OSes offer only one charset per language, and most OSes have only one charset each for many languages. Note too the remark above about Chinese.

7.1.1 Locales under Linux

Modern Linux uses the XPG¹³ locale specifications which have the form ‘en_GB’, ‘en_GB.UTF-8’, ‘aa_ER.UTF-8@saaho’, ‘de_AT.iso885915@euro’, the components being in the order listed above. (See man locale and locale -a for more details.) Similar schemes are used by most Unix-alikes: some (including some distributions of Linux) use ‘.utf8’ rather than ‘.UTF-8’.

7.1.2 Locales under Windows

Some care is needed with Windows’ locale names. For example, chinese is Traditional Chinese and not Simplified Chinese as used in most of the Chinese-speaking world.

7.1.3 Locales under OS X

OS X supports locales in its own particular way, but the R GUI tries to make this easier for users. See http://developer.apple.com/documentation/MacOSX/Conceptual/BPInternational/ for how users can set their locales. As with Windows, end users will generally only see lists of languages/territories. Users of R in a terminal may need to set the locale to something like ‘en_GB.UTF-8’ if it defaults to ‘C’ (as it often does when logging it remotely and in batch jobs).

Internally OS X uses a form similar to Linux. It is based on ICU locales IDs (http://userguide.icu-project.org/locale) and not XPG ones, but utilities such as Sys.setlocale() do now normally accept XPG forms. So there are locales like de_AT.ISO8859-15 (German in Austria in Latin-9, which covers the Euro): the main difference from other Unix-alikes is that where a character set is not specified it is assumed to be UTF-8.

7.2 Localization of messages

The preferred language for messages is by default taken from the locale. This can be overridden first by the setting of the environment variable LANGUAGE and then¹⁴ by the environment variables LC_ALL, LC_MESSAGES and LANG. (The last three are normally used to set the locale and so should not be needed, but the first is only used to select the language for messages.) The code tries hard to map locales to languages, but on some systems (notably Windows) the locale names needed for the environment variable LC_ALL do not all correspond to XPG language names and so LANGUAGE may need to be set. (One example is ‘LC_ALL=es’ on Windows which sets the locale to Estonian and the language to Spanish.)

It is usually possible to change the language once R is running via (not Windows)

Sys.setlocale("LC_MESSAGES",
"new_locale")

, or by setting an environment variable such as LANGUAGE, provided¹⁵ the language you are changing to can be output in the current character set. But this is OS-specific, and has been known to stop working on an OS upgrade.

Messages are divided into domains, and translations may be available for some or all messages in a domain. R makes use of the following domains.

Dividing up the messages in this way allows R to be extensible: as packages are loaded, their message translation catalogues can be loaded too.

Translations are looked for by domain according to the currently specified language, as specifically as possible, so for example an Austrian (‘de_AT’) translation catalogue will be used in preference to a generic German one (‘de’) for an Austrian user. However, if a specific translation catalogue exists but does not contain a translation, the less specific catalogues are consulted. For example, R has catalogues for ‘en_GB’ that translate the Americanisms (e.g., ‘gray’) in the standard messages into English.¹⁶ Two other examples: there are catalogues for ‘es’, which is Spanish as written in Spain and these will by default also be used in Spanish-speaking Latin American countries, and also for ‘pt_BR’, which are used for Brazilian locales but not for locales specifying Portugal.

Translations in the right language but the wrong charset be made use of by on-the-fly re-encoding. The LANGUAGE variable (only) can be a colon-separated list, for example ‘se:de’, giving a set of languages in decreasing order of preference. One special value is ‘en@quot’, which can be used in a UTF-8 locale to have American error messages with pairs of quotes translated to Unicode directional quotes.

If no suitable translation catalogue is found or a particular message is not translated in any suitable catalogue, ‘English’¹⁷ is used.

8 Choosing between 32- and 64-bit builds

Many current CPUs have both 32- and 64-bit sets of instructions: this has long been true for UltraSparc and more recently for MIPS, PPC and ‘x86_64’ (sometimes known as ‘amd64’ and ‘Intel64’ and earlier as ‘EM64T’: practically all current ‘ix86’ CPUs support this set of instructions). Most OSes running on such CPUs offer the choice of building a 32-bit or a 64-bit version of R (and details are given below under specific OSes). For most a 32-bit version is the default, but for some (e.g., ‘x86_64’ Linux and (Mac) OS X >= 10.6) 64-bit is.

All current versions of R use 32-bit integers and IEC 60559¹⁸ double-precision reals, and so compute to the same precision¹⁹ and with the same limits on the sizes of numerical quantities. The principal difference is in the size of the pointers.

So, for speed you may want to use a 32-bit build, but to handle large datasets (and perhaps large files) a 64-bit build. You can often build both and install them in the same place: See Sub-architectures. (This is done in the OS X and Windows binary distributions.)

Even on 64-bit builds of R there are limits on the size of R objects (see help("Memory-limits"), some of which stem from the use of 32-bit integers (especially in FORTRAN code). On all builds of R, the maximum length (number of elements) of a vector is 2^{31}-1, about 2 billion, and on 64-bit builds the size of a block of memory allocated is limited to 2^{34}-1 bytes (8GB). It is anticipated these will be raised eventually²⁰ but the need for 8GB objects is (when this was written in 2011) exceptional.

9 The standalone Rmath library

The routines supporting the distribution and special²¹ functions in R and a few others are declared in C header file Rmath.h. These can be compiled into a standalone library for linking to other applications. (Note that they are not a separate library when R is built, and the standalone version differs in several ways.)

The makefiles and other sources needed are in directory src/nmath/standalone, so the following instructions assume that is the current working directory (in the build directory tree on a Unix-alike if that is separate from the sources).

Rmath.h contains ‘R_VERSION_STRING’, which is a character string containing the current R version, for example "2.15.0".

There is full access to R’s handling of NaN, Inf and -Inf via special versions of the macros and functions

There is no support for R’s notion of missing values, in particular not for NA_INTEGER nor the distinction between NA and NaN for doubles.

A little care is needed to use the random-number routines. You will need to supply the uniform random number generator

or use the one supplied (and with a shared library or DLL you will have to use the one supplied, which is the Marsaglia-multicarry with an entry point

The facilities to change the normal random number generator are available through the constant N01_kind. This takes values from the enumeration type

9.1 Unix-alikes

If R has not already be made in the directory tree, configure must be run as described in the main build instructions.

will make standalone libraries libRmath.a and libRmath.so (libRmath.dylib on Mac OS X): ‘make static’ and ‘make shared’ will create just one of them.

NB: certain compilers are unable to do compile-time IEC 60559 arithmetic and so cannot compile mlutils.c and several other files. The known example is old versions of Sun’s cc (e.g. Forte 6 and 7).

and link against ‘-lRmath’ (and ‘-lm’ if needed on your OS). The example file test.c does nothing useful, but is provided to test the process (via make test). Note that you will probably not be able to run it unless you add the directory containing libRmath.so to the LD_LIBRARY_PATH environment variable.

will (un)install the header Rmath.h and shared and static libraries (if built). Both prefix= and DESTDIR are supported, together with more precise control as described for the main build.

On some systems ‘make install-strip’ will install a stripped shared library.

9.2 Windows

You need to set up²² almost all the tools to make R and then run (in a Unix-like shell)

This creates a static library libRmath.a and a DLL Rmath.dll. If you want an import library libRmath.dll.a (you don’t need one), use

and link against ‘-lRmath’. This will use the first found of libRmath.dll.a, libRmath.a and Rmath.dll in that order, so the result depends on which files are present. You should be able to force static or dynamic linking via

or by linking to explicit files (as in the ‘test’ target in Makefile.win: this makes two executables, test.exe which is dynamically linked, and test-static.exe, which is statically linked).

It is possible to link to Rmath.dll using other compilers, either directly or via an import library: if you make a MinGW import library as above, you will create a file Rmath.def which can be used (possibly after editing) to create an import library for other systems such as Visual C++.

to ensure that the constants like NA_REAL are linked correctly. (Auto-import will probably work with MinGW, but it is better to be sure. This is likely to also work with VC++, Borland and similar compilers.)

Appendix A Essential and useful other programs under a Unix-alike

This appendix gives details of programs you will need to build R on Unix-like platforms, or which will be used by R if found by configure.

Remember that some package management systems (such as RPM and deb) make a distinction between the user version of a package and the development version. The latter usually has the same name but with the extension ‘-devel’ or ‘-dev’: you need both versions installed.

A.1 Essential programs and libraries

You need a means of compiling C and FORTRAN 77 (see Using FORTRAN). Some add-on packages also need a C++ compiler. Your C compiler should be IEC 60059²³, POSIX 1003.1 and C99-compliant.²⁴ R tries to choose suitable flags for the C compilers it knows about, but you may have to set CC or CFLAGS suitably. For recent versions of gcc with glibc this means including -std=gnu99²⁵. If the compiler is detected as gcc, -std=gnu99 will be appended to CC unless it conflicts with a setting of CFLAGS. (Note that options essential to run the compiler even for linking, such as those to set the architecture, should be specified as part of CC rather than in CFLAGS.)

Unless you do not want to view graphs on-screen (or use a Mac) you need ‘X11’ installed, including its headers and client libraries. For recent Fedora distributions it means (at least) RPMs ‘libX11’, ‘libX11-devel’, ‘libXt’ and ‘libXt-devel’. On Debian we recommend the meta-package ‘xorg-dev’. If you really do not want these you will need to explicitly configure R without X11, using --with-x=no.

The command-line editing (and command completion) depends on the GNU readline library: version 4.2 or later is needed for all the features to be enabled. Otherwise you will need to configure with --with-readline=no (or equivalent).

A suitably comprehensive iconv function is essential. The R usage requires iconv to be able to translate between "latin1" and "UTF-8", to recognize "" (as the current encoding) and "ASCII", and to translate to and from the Unicode wide-character formats "UCS-[24][BL]E" — this is true for glibc but not of most commercial Unixes. However, you can make use of GNU libiconv (possibly as a plug-in replacement: see http://www.gnu.org/software/libiconv/).

An implementation of XDR is required. This is part of RPC and historically has been part of libc on a Unix-alike: however some builds²⁶ of

glibc
2.14

hide it. The intention seems to be that the TI-RPC library be used instead, in which case libtirpc (and its development version) needs to be installed, and its headers need to be on the C include path (and configure tries /usr/include/tirpc if the headers are not found on the standard include path). The R sources contain a simple implementation of XDR which in recent versions can be used on platforms with 32-bit or 64-bit long (and earlier ones will fail to compile unless long is 32-bit).

The OS needs to have enough support²⁷ for wide-character types: this is checked at configuration.

A tar program is needed to unpack the sources and packages (including the recommended packages). A version²⁸ that can automagically detect compressed archives is preferred for use with untar(): the configure script looks for gtar and gnutar before tar: use environment variable TAR to override this.

There need to be suitable versions of the tools grep and sed: the problems are usually with old AT&T and BSD variants. configure will try to find suitable versions (including looking in /usr/xpg4/bin which is used on some commercial Unixes).

You will not be able to build most of the manuals unless you have makeinfo version 4.7 or later installed, and if not some of the HTML manuals will be linked to CRAN. To make PDF versions of the manuals you will also need file texinfo.tex installed (which is part of the GNU texinfo distribution but is often made part of the TeX package in re-distributions) as well as texi2dvi.²⁹ Further, the versions of texi2dvi and texinfo.tex need to be compatible: we have seen problems with older TeX distributions (TeXLive 2007 and MiKTeX 2.8) used with texinfo 4.13.

The PDF documentation (including doc/NEWS.pdf) and building vignettes needs tex and latex, or pdftex and pdflatex. We require LaTeX version 2005/12/01 or later (for UTF-8 support). Building PDF package manuals (including the R reference manual) and vignettes is sensitive to the version of the LaTeX package hyperref and we recommend that the TeX distribution used is keep up-to-date. A number of LaTeX packages are required (including url.sty, and listings.sty) and others such as hyperref and inconsolata are desirable (and without them you will need to change R’s defaults: see Making the manuals).

If you want to build from the R Subversion repository you need both makeinfo and pdflatex.

The essential programs should be in your PATH at the time configure is run: this will capture the full paths.

A.2 Useful libraries and programs

The ability to use translated messages makes use of gettext and most likely needs GNU gettext: you do need this to work with new translations, but otherwise the version contained in the R sources will be used if no suitable external gettext is found.

The ‘modern’ version of the X11(), jpeg(), png() and tiff() graphics devices uses the cairo and (optionally) Pango libraries. Cairo version 1.2.0 or later is required. Pango needs to be at least version 1.10, and 1.12 is the earliest version we have tested. (For Fedora users we believe the pango-devel RPM and its dependencies suffice.) R checks for pkg-config, and uses that to check first that the ‘pangocairo’ package is installed (and if not, ‘cairo’) and if additional flags are needed for the ‘cairo-xlib’ package, then if suitable code can be compiled. These tests will fail if pkg-config is not installed, and are likely to fail if cairo was built statically (unusual). Most systems with Gtk+ 2.8 or later installed will have suitable libraries. OS X comes with none of these libraries, but cairo support (without Pango) has been added to the binary distribution: pkg-config is still needed and can be installed from the sources.

For the best font experience with these devices you need suitable fonts installed: Linux users will want the urw-fonts package. On platforms which have it available, the msttcorefonts package³⁰ provides TrueType versions of Monotype fonts such as Arial and Times New Roman. Another useful set of fonts is the ‘liberation’ TrueType fonts available at https://www.redhat.com/promo/fonts/,³¹ which cover the Latin, Greek and Cyrillic alphabets plus a fair range of signs. These share metrics with Arial, Times New Roman and Courier New, and contain fonts rather similar to the first two (http://en.wikipedia.org/wiki/Liberation_fonts). Then there is the ‘Free UCS Outline Fonts’ project (http://www.gnu.org/software/freefont/) which are OpenType/TrueType fonts based on the URW fonts but with extended Unicode coverage. See the R help on X11 on selecting such fonts.

The bitmapped graphics devices jpeg(), png() and tiff() need the appropriate headers and libraries installed: jpeg (version 6b or later, or libjpeg-turbo) or libpng (version 1.2.7 or later, including 1.4.x and 1.5.x) and zlib or libtiff (any recent version of 3.x.y – 3.9.[45] have been tested) respectively. They also need support for either X11 or cairo (see above).

If you have them installed (including the appropriate headers and of suitable versions), system versions of zlib, libbz2 and PCRE will be used if specified by --with-system-zlib (version 1.2.3 or later), --with-system-bzlib or --with-system-pcre (version 8.10 or later, preferably 8.21 which is what is supplied with R): otherwise versions in the R sources will be compiled in. As the latter suffice and are tested with R you should not need to change this.

liblzma from xz-utils version 4.999 or later (preferably 5.0.0 or later) will be used if installed: the version in the R sources can be selected instead by configuring with --with-system-xz=no.

Use of the X11 clipboard selection requires the Xmu headers and libraries. These are normally part of an X11 installation (e.g. the Debian meta-package ‘xorg-dev’), but some distributions have split this into smaller parts, so for example recent versions of Fedora require the ‘libXmu’ and ‘libXmu-devel’ RPMs.

Some systems (notably OS X and at least some FreeBSD systems) have inadequate support for collation in multibyte locales. It is possible to replace the OS’s collation support by that from ICU (International Components for Unicode, http://site.icu-project.org/), and this provides much more precise control over collation on all systems. ICU is available as sources and as binary distributions for (at least) most Linux distributions, Solaris, FreeBSD and AIX, usually as libicu or icu4c. It will be used by default where available (including on OS X >= 10.4): should a very old or broken version of ICU be found this can be suppressed by --without-ICU.

The bitmap and dev2bitmap devices and also embedFonts() use ghostscript (http://www.cs.wisc.edu/~ghost). This should either be in your path when the command is run, or its full path specified by the environment variable R_GSCMD at that time.

A.2.1 Tcl/Tk

The tcltk package needs Tcl/Tk >= 8.4 installed: the sources are available at http://www.tcl.tk/. To specify the locations of the Tcl/Tk files you may need the configuration options

or use the configure variables TCLTK_LIBS and TCLTK_CPPFLAGS to specify the flags needed for linking against the Tcl and Tk libraries and for finding the tcl.h and tk.h headers, respectively. If you have both 32- and 64-bit versions of Tcl/Tk installed, specifying the paths to the correct config files may be necessary to avoid confusion between them.

Versions of Tcl/Tk up to 8.5.10 have been tested (including most versions of 8.4.x, but not recently).

A.2.2 Java support

configure looks for Java support on the host system, and if it finds it sets some settings which are useful for Java-using packages. JAVA_HOME can be set during the configure run to point to a specific JRE/JDK.

Principal amongst these are setting some library paths to the Java libraries and JVM, which are stored in environment variable R_JAVA_LD_LIBRARY_PATH in file R_HOME/etc/ldpaths (or a sub-architecture-specific version). A typical setting for ‘x86_64’ Linux is

Note that this unfortunately depends on the exact version of the JRE/JDK installed, and so may need updating if the Java installation is updated. This can be done by running R CMD javareconf. The script re-runs Java detection in a manner similar to that of the configure script and updates settings in both Makeconf and R_HOME/etc/ldpaths. See R CMD javareconf --help for details.

Another alternative of overriding those setting is to set R_JAVA_LD_LIBRARY_PATH (e.g. in ~/.Renviron), or use /etc/ld.so.conf to specify the Java runtime library paths to the system. Other settings are recorded in etc/Makeconf (or a sub-architecture-specific version), e.g.

where ‘JAVA_LIBS’ contains flags necessary to link JNI programs. Some of the above variables can be queried using R CMD config.

A.3 Linear algebra

A.3.1 BLAS

The linear algebra routines in R can make use of enhanced BLAS (Basic Linear Algebra Subprograms, http://www.netlib.org/blas/faq.html) routines. However, these have to be explicitly requested at configure time: R provides an internal BLAS which is well-tested and will be adequate for most uses of R.

You can specify a particular BLAS library via a value for the configuration option --with-blas and not to use an external BLAS library by --without-blas (the default). If --with-blas is given with no =, its value is taken from the environment variable BLAS_LIBS, set for example in config.site. If neither the option nor the environment variable supply a value, a search is made for a suitable BLAS. If the value is not obviously a linker command (starting with a dash or giving the path to a library), it is prefixed by ‘-l’, so

is an instruction to link against ‘-lfoo’ to find an external BLAS (which needs to be found both at link time and run time).

The configure code checks that the external BLAS is complete (it must include all double precision and double complex routines, as well as LSAME), and appears to be usable. However, an external BLAS has to be usable from a shared object (so must contain position-independent code), and that is not checked.

Some enhanced BLASes are compiler-system-specific (sunperf on Solaris³², libessl on IBM, vecLib on OS X). The correct incantation for these is usually found via --with-blas with no value on the appropriate platforms.

Some of the external BLASes are multi-threaded. One issue is that R profiling (which uses the SIGPROF signal) may cause problems, and you may want to disable profiling if you use a multi-threaded BLAS. Note that using a multi-threaded BLAS can result in taking more CPU time and even more elapsed time (occasionally dramatically so) than using a similar single-threaded BLAS.

Note that under Unix (but not under Windows) if R is compiled against a non-default BLAS and --enable-BLAS-shlib is not used, then all BLAS-using packages must also be. So if R is re-built to use an enhanced BLAS then packages such as quantreg will need to be re-installed.

R relies on IEC 60559 compliance of an external BLAS. This can be broken if for example the code assumes that terms with a zero factor are always zero and do not need to be computed—whereas x*0 can be NaN. This is checked in the test suite.

A.3.1.1 ATLAS

ATLAS (http://math-atlas.sourceforge.net/) is a “tuned” BLAS that runs on a wide range of Unix-alike platforms. Unfortunately it is usually built as a static library that on some platforms cannot be used with shared objects such as are used in R packages. Be careful when using pre-built versions of ATLAS (they seem to work on ‘ix86’ platforms, but not always on ‘x86_64’ ones).

For systems with multiple CPU cores it is possible to use a multi-threaded version of ATLAS, by specifying

Consult its file INSTALL.txt for how to build ATLAS with position-independent code (at least on version 3.8.0 and later): that file also describes how to build ATLAS as a shared library.

ATLAS can also be used on Windows: see see Getting the source files when building from source, and R Windows FAQ for adding pre-compiled support to binary versions.

A.3.1.2 ACML

For ‘x86_64’ and ‘i686’ processors under Linux there is the AMD Core Math Library (ACML) http://www.amd.com/acml. For the gcc version we could use

if the appropriate library directory (such as /opt/acml5.1.0/gfortran64/lib) is in the LD_LIBRARY_PATH. For other compilers, see the ACML documentation. There is a multithreaded Linux version of ACML available for recent versions of gfortran. To make use of this you will need something like

See see Shared BLAS for an alternative (and in many ways preferable) way to use ACML.

The version last tested (5.1.0) failed the reg-BLAS.R test in its handling of NAs.

A.3.1.3 Goto BLAS

Dr Kazushige Goto wrote another tuned BLAS which is available for several processors and OSes. The current version is known as GotoBLAS2, and has (in November 2010) been re-released under a much less restrictive licence. Source code can be obtained from http://www.tacc.utexas.edu/tacc-projects/gotoblas2/

See see Shared BLAS for an alternative (and in many ways preferable) way to use it.

Our understanding is that this project is now frozen and so will not be updated for CPUs released since mid-2010. However, OpenBLAS (http://xianyi.github.com/OpenBLAS/) is a descendant project.

A.3.1.4 Intel MKL

For Intel processors under Linux, there is Intel’s Math Kernel Library (http://www.intel.com/software/products/mkl/). You are strongly encouraged to read the MKL User’s Guide, which is installed with the library, before attempting to link to MKL. There are also versions of MKL for Mac OS X and Windows, but they do not work with the standard compilers used for R on those platforms.

The MKL interface has changed several times, and may change again: the following notes apply exactly only to version 10.0.

Version 10 of MKL supports two linking models: the default model, which is backward compatible with version 9 (see below), and the pure layered model. The layered model gives the user fine-grained control over four different library layers: interface, threading, computation, and run-time library support. Some examples of linking to MKL using this layered model are given below. (These examples are for GCC compilers on ‘x86_64’.) The choice of interface layer is important on ‘x86_64’ since the Intel Fortran compiler returns complex values in different registers from the GNU Fortran compiler. You must therefore use the interface layer that matches your compiler (mkl_intel* or mkl_gf*).

The order of the libraries is important. The option --with-lapack is used since MKL contains a tuned copy of LAPACK as well as BLAS (see LAPACK), although this (and the corresponding library) can be omitted.

Threaded MKL may be used (according to Zhang Zhang of Intel) by replacing the line defining the variable MKL with (Intel OMP)

The default number of threads will be chosen by the OpenMP software, but can be controlled by setting OMP_NUM_THREADS or MKL_NUM_THREADS.

The default linking model, which was also used by version 9 of MKL, can be used by

but this may not match your compiler on a 64-bit platform. This is multi-threaded, but in version 9 the number of threads defaults to 1. It can be increased by setting OMP_NUM_THREADS. (Thanks to Andy Liaw for the information.)

A.3.1.5 Shared BLAS

The BLAS library will be used for many of the add-on packages as well as for R itself. This means that it is better to use a shared/dynamic BLAS library, as most of a static library will be compiled into the R executable and each BLAS-using package.

R offers the option of compiling the BLAS into a dynamic library libRblas stored in R_HOME/lib and linking both R itself and all the add-on packages against that library.

This is the default on all platforms except AIX unless an external BLAS is specified and found: for the latter it can be used by specifying the option --enable-BLAS-shlib, and it can always be disabled via --disable-BLAS-shlib.

Another option to change the BLAS in use is to symlink a dynamic BLAS library (such as ACML or Goto’s) to R_HOME/lib/libRblas.so. For example, just

will change the BLAS in use to multithreaded ACML. A similar link works for recent versions of the Goto BLAS and perhaps for MKL (provided the appropriate lib directory is in the run-time library path or ld.so cache).

A.3.2 LAPACK

Provision is made for using an external LAPACK library, principally to cope with BLAS libraries which contain a copy of LAPACK (such as sunperf on Solaris, vecLib on OS X and ACML on ‘ix86’/‘x86_64’ Linux). However, the likely performance gains are thought to be small (and may be negative), and the default is not to search for a suitable LAPACK library, and this is definitely not recommended. You can specify a specific LAPACK library or a search for a generic library by the configuration option --with-lapack. The default for --with-lapack is to check the BLAS library and then look for an external library ‘-llapack’. Sites searching for the fastest possible linear algebra may want to build a LAPACK library using the ATLAS-optimized subset of LAPACK. To do so specify something like

since the ATLAS subset of LAPACK depends on libcblas. A value for --with-lapack can be set via the environment variable LAPACK_LIBS, but this will only be used if --with-lapack is specified (as the default value is no) and the BLAS library does not contain LAPACK.

Since ACML contains a full LAPACK, if selected as the BLAS it can be used as the LAPACK via --with-lapack.

If you do use --with-lapack, be aware of potential problems with bugs in the LAPACK 3.0 sources (or in the posted corrections to those sources). In particular, bugs in DGEEV and DGESDD have resulted in error messages such as

. Other potential problems are incomplete versions of the libraries, seen several times over the years. For problems compiling LAPACK using recent versions of gcc on ‘ix86’ Linux, see New platforms.

Please do bear in mind that using --with-lapack is ‘definitely not recommended’: it is provided only because it is necessary on some platforms. Reporting problems where it is used unnecessarily will simply irritate the R helpers.

A.3.3 Caveats

As with all libraries, you need to ensure that they and R were compiled with compatible compilers and flags. For example, this has meant that on Sun Sparc using the native compilers the flag -dalign is needed so sunperf can be used.

On some systems it is necessary that an external BLAS/LAPACK was built with the same FORTRAN compiler used to build R: known problems are with R built with gfortran, see Using gfortran.

Appendix B Configuration on a Unix-alike

B.1 Configuration options

will give a list. Probably the most important ones not covered elsewhere are (defaults in brackets)

You will want to use --disable-R-profiling if you are building a profiled executable of R (e.g. with ‘-pg)’.

Flag --enable-R-shlib causes the make process to build R as a dynamic (shared) library, typically called libR.so, and link the main R executable R.bin against that library. This can only be done if all the code (including system libraries) can be compiled into a dynamic library, and there may be a performance³³ penalty. So you probably only want this if you will be using an application which embeds R. Note that C code in packages installed on an R system linked with --enable-R-shlib is linked against the dynamic library and so such packages cannot be used from an R system built in the default way. Also, because packages are linked against R they are on some OSes also linked against the dynamic libraries R itself is linked against, and this can lead to symbol conflicts.

If you need to re-configure R with different options you may need to run make clean or even make distclean before doing so.

B.2 Compressed and uncompressed pointers

By default, pqR represents objects internally using ordinary pointers (machine addresses), which are commonly either 64 bits or 32 bits in size. As an alternative, pqR can instead use compressed pointers, which are 32 bits in size on all platforms. On a 64-bit platform, this reduces memory usage, considerably in some cases. On a 32-bit platform, there is also some reduction in memory usage, though not by as much. The cost is that some programs run a bit slower, due to the overhead of decoding the compressed pointers, though other programs run faster, due to the smaller memory usage.

To enable use of compressed pointers, give the --enable-compressed-pointers option to ./configure.

That option is probably all that is needed to use compressed pointers, but programs that use a large amount of memory (many Gigabytes), in the form of a huge number of fairly small objects, may need to increase the default limit on the number of “segments” used for compressed pointers. This can be done by adding, for example, -DSGGC_MAX_SEGMENTS=50000000 to CFLAGS. On Intel machines (and perhaps others), such a large limit may be undesirable otherwise, since it reduces the size of a program that can be handled with the “medium” memory model, though problems are still unlikely.

If uncompressed pointers are used, on a platform with 64-bit pointers, the --enable-aux-for-attrib option to ./configure will alter the representation of objects so that attributes are stored as “auxiliary information”. This allows more compact representations of some objects, with possible speed and memory benefits.

The --enable-compressed-pointers and --enable-aux-for-attrib options affect how C code used with .Call and .External is compiled. C code compiled with one setting for these options must not be used by a version of pqR compiled with other settings.

B.3 Helper threads and task merging

Support for computations in helper threads and for merging of tasks is enabled by default.

Use of helper threads may be disabled with the --disable-helper-threads configuration option. Disabling support for helper threads will produce a small speed improvement, compared to running pqR with helper thread support enabled, but with no helper threads. The --disable-helper-threads option will also allow pqR to be built on a system that does not support OpenMP.

Merging of tasks may be disabled with the --disable-task-merging configuration option. Currently, code for all possible merged tasks (2744 of them) is generated at compile time. This code occupies space at run time, and takes time and space to generate when pqR is compiled. On very small systems, it may therefore be desirable (or essential) to disable task merging.

The whole helpers apparatus, including deferred evaluation even with no helper threads and no task merging, can be disabled with the --disable-deferred-evaluation configuraton option. This will produce a further slight speed improvement in situations where neither helper threads nor task merging are useful.

If the BLAS routines used for matrix multiplication are not thread-safe, the BLAS_in_helpers=FALSE option (whose default can be set by configure) should be used, to prevent tasks that call the BLAS from being run in helper threads. This option may also be useful if the BLAS is multi-threaded and runs inefficiently (even if correctly) when several BLAS routines are running in parallel. You may also want to set the mat_mult_with_BLAS option as desired. The defaults for these options are BLAS_in_helpers=FALSE and mat_mult_with_BLAS=NA when --with-blas is given as an argument to configure, and BLAS_in_helpers=TRUE and mat_mult_with_BLAS=FALSE when there is no --with-blas argument. See help(options) for more on the meaning of these options.

B.4 Internationalization support

Translation of messages is supported via GNU gettext unless disabled by the configure option --disable-nls. The configure report will show NLS as one of the ‘Additional capabilities’ if support has been compiled in, and running in an English locale (but not the C locale) will include

B.5 Configuration variables

If you need or want to set certain configure variables to something other than their default, you can do that by either editing the file config.site (which documents many of the variables you might want to set: others can be seen in file etc/Renviron.in) or on the command line as

If you are building in a directory different from the sources, there can be copies of config.site in the source and the build directories, and both will be read (in that order). In addition, if there is a file ~/.R/config (or failing that) ~/.Rconfig), it is read between the config.site files in the source and the build directories.

There is also a general autoconf mechanism for config.site files, which are read before any of those mentioned in the previous paragraph. This looks first at a file specified by the environment variable CONFIG_SITE, and if not is set at files such as /usr/local/share/config.site and /usr/local/etc/config.site in the area (exemplified by /usr/local) where R would be installed.

These variables are precious, implying that they do not have to be exported to the environment, are kept in the cache even if not specified on the command line, checked for consistency between two configure runs (provided that caching is used), and are kept during automatic reconfiguration as if having been passed as command line arguments, even if no cache is used.

See the variable output section of configure --help for a list of all these variables.

If you find you need to alter configure variables, it is worth noting that some settings may be cached in the file config.cache, and it is a good idea to remove that file (if it exists) before re-configuring. Note that caching is turned off by default: use the command line option --config-cache (or -C) to enable caching.

B.5.1 Setting paper size

One common variable to change is R_PAPERSIZE, which defaults to ‘a4’, not ‘letter’. (Valid values are ‘a4’, ‘letter’, ‘legal’ and ‘executive’.)

This is used both when configuring R to set the default, and when running R to override the default. It is also used to set the paper size when making PDF manuals.

The configure default will most often be ‘a4’ if R_PAPERSIZE is unset. (If the (Debian Linux) program paperconf is found or the environment variable PAPERSIZE is set, these are used to produce the default.)

B.5.2 Setting the browsers

Another precious variable is R_BROWSER, the default HTML browser, which should take a value of an executable in the user’s path or specify a full path.

B.5.3 Compilation flags

If you have libraries and header files, e.g., for GNU readline, in non-system directories, use the variables LDFLAGS (for libraries, using ‘-L’ flags to be passed to the linker) and CPPFLAGS (for header files, using ‘-I’ flags to be passed to the C/C++ preprocessors), respectively, to specify these locations. These default to ‘-L/usr/local/lib’ (LDFLAGS, ‘-L/usr/local/lib64’ on most 64-bit Linux OSes) and ‘-I/usr/local/include’ (CPPFLAGS) to catch the most common cases. If libraries are still not found, then maybe your compiler/linker does not support re-ordering of -L and -l flags (this has been reported to be a problem on HP-UX with the native cc). In this case, use a different compiler (or a front end shell script which does the re-ordering).

These flags can also be used to build a faster-running version of R. On most platforms using gcc, having ‘-O3’ in CFLAGS and FFLAGS produces worthwhile performance gains with gcc and gfortran, though it is also possible that this will create bugs due to over-enthusiastic optimization, or produce code that is slower than with ‘-O2’.

On systems using the GNU linker (especially those using R as a shared library), it is likely that including ‘-Wl,-O1’ in LDFLAGS is worthwhile, and ‘'-Bdirect,--hash-style=both,-Wl,-O1'’ is recommended at http://lwn.net/Articles/192624/.

Tuning compilation to a specific CPU family (e.g. ‘-mtune=native’ for gcc) can give worthwhile performance gains, especially on older architectures such as ‘ix86’.

B.5.4 Making manuals

The default settings for making the manuals are controlled by R_RD4PDF and R_PAPERSIZE.

B.6 Setting the shell

By default the shell scripts such as R will be ‘#!/bin/sh’ scripts (or using the SHELL chosen by configure). This is almost always satisfactory, but on a few systems /bin/sh is not a Bourne shell or clone, and the shell to be used can be changed by setting the configure variable R_SHELL to a suitable value (a full path to a shell, e.g. /usr/local/bin/bash).

B.7 Using make

To compile R, you will most likely find it easiest to use GNU make, although the Sun make works on Solaris, as does the native FreeBSD make. The native make has been reported to fail on SGI Irix 6.5 and Alpha/OSF1 (aka Tru64).

To build in a separate directory you need a make that uses the VPATH variable, for example GNU make, or Sun make on Solaris 7 or later.

If you want to use a make by another name, for example if your GNU make is called ‘gmake’, you need to set the variable MAKE at configure time, for example

B.8 Using FORTRAN

To compile R, you need a FORTRAN compiler. The default is to search for f95, fort, xlf95, ifort, ifc, efc, pgf95 lf95, gfortran, ftn, g95, f90, xlf90, pghpf, pgf90, epcf90, g77, f77, xlf, frt, pgf77, cf77, fort77, fl32, af77 (in that order)³⁴, and use whichever is found first; if none is found, R cannot be compiled. However, if CC is gcc, the matching FORTRAN compiler (g77 for gcc 3 and gfortran for gcc 4) is used if available.

The search mechanism can be changed using the configure variable F77 which specifies the command that runs the FORTRAN 77 compiler. If your FORTRAN compiler is in a non-standard location, you should set the environment variable PATH accordingly before running configure, or use the configure variable F77 to specify its full path.

If your FORTRAN libraries are in slightly peculiar places, you should also look at LD_LIBRARY_PATH or your system’s equivalent to make sure that all libraries are on this path.

Note that only FORTRAN compilers which convert identifiers to lower case are supported.

You must set whatever compilation flags (if any) are needed to ensure that FORTRAN integer is equivalent to a C int pointer and FORTRAN double precision is equivalent to a C double pointer. This is checked during the configuration process.

Some of the FORTRAN code makes use of COMPLEX*16 variables, which is a Fortran 90 extension. This is checked for at configure time³⁵, but you may need to avoid compiler flags³⁶ asserting FORTRAN 77 compliance.

It may be possible to use f2c, the FORTRAN-to-C converter (http://www.netlib.org/f2c), via a script. (An example script is given in scripts/f77_f2c: this can be customized by setting the environment variables F2C, F2CLIBS, CC and CPP.) You will need to ensure that the FORTRAN type integer is translated to the C type int. Normally f2c.h contains ‘typedef long int integer;’, which will work on a 32-bit platform but not on a 64-bit platform. If your compiler is not gcc you will need to set FPICFLAGS appropriately.

B.8.1 Using gfortran

gfortran is the F95 compiler that is part of gcc 4.x.y. There were problems compiling R with the first release (gcc 4.0.0) and more with pre-releases, but these are resolved in later versions.

On Linux ‘x86_64’ systems there is an incompatibility in the return conventions for double-complex functions between gfortran and g77 which results in the final example in example(eigen) hanging or segfaulting under external BLASs built under g77. This should be detected by a configure test.

The default FFLAGS and FCFLAGS chosen (by autoconf) for a GNU FORTRAN compiler is ‘-g -O2’. This has caused problems (segfaults and infinite loops) on ‘x86_64’ Linux in the past, but seems fine with gfortran 4.4.4 and later: for gfortran 4.3.x set FFLAGS and FCFLAGS to use at most ‘-O’.

B.9 Compile and load flags

A wide range of flags can be set in the file config.site or as configure variables on the command line. We have already mentioned

Library paths specified as -L/lib/path in LDFLAGS are collected together and prepended to LD_LIBRARY_PATH (or your system’s equivalent), so there should be no need for -R or -rpath flags.

Variables such as CPICFLAGS are determined where possible by configure. Some systems allows two types of PIC flags, for example ‘-fpic’ and ‘-fPIC’, and if they differ the first allows only a limited number of symbols in a shared object. Since R as a shared library has about 6200 symbols, if in doubt use the larger version.

To compile a profiling version of R, one might for example want to use ‘MAIN_CFLAGS=-pg’, ‘MAIN_FFLAGS=-pg’, ‘MAIN_LDFLAGS=-pg’ on platforms where ‘-pg’ cannot be used with position-independent code.

Beware: it may be necessary to set CFLAGS and FFLAGS in ways compatible with the libraries to be used: one possible issue is the alignment of doubles, another is the way structures are passed.

On some platforms configure will select additional flags for CFLAGS, CPPFLAGS, FFLAGS, CXXFLAGS and LIBS in R_XTRA_CFLAGS (and so on). These are for options which are always required, for example to force IEC 60559 compliance.

Appendix C Platform notes

This section provides some notes on building R on different Unix-alike platforms. These notes are based on tests run on one or two systems in each case with particular sets of compilers and support libraries. Success in building R depends on the proper installation and functioning of support software; your results may differ if you have other versions of compilers and support libraries.

Older versions of this manual (for R < 2.10.0) contain notes on platforms such as HP-UX, IRIX and Alpha/OSF1 for which we have had no recent reports.

C.1 X11 issues

The ‘X11()’ graphics device is the one started automatically on Unix-alikes when plotting. As its name implies, it displays on a (local or remote) X server, and relies on the services provided by the X server.

The ‘modern’ version of the ‘X11()’ device is based on ‘cairo’ graphics and (in most implementations) uses ‘fontconfig’ to pick and render fonts. This is done on the server, and although there can be selection issues, they are more amenable than the issues with ‘X11()’ discussed in the rest of this section.

When X11 was designed, most displays were around 75dpi, whereas today they are of the order of 100dpi or more. If you find that X11() is reporting³⁸ missing font sizes, especially larger ones, it is likely that you are not using scalable fonts and have not installed the 100dpi versions of the X11 fonts. The names and details differ by system, but will likely have something like Fedora’s

and you need to ensure that the ‘-100dpi’ versions are installed and on the X11 font path (check via xset -q). The ‘X11()’ device does try to set a pointsize and not a pixel size: laptop users may find the default setting of 12 too large (although very frequently laptop screens are set to a fictitious dpi to appear like a scaled-down desktop screen).

More complicated problems can occur in non-Western-European locales, so if you are using one, the first thing to check is that things work in the C locale. The likely issues are a failure to find any fonts or glyphs being rendered incorrectly (often as a pair of ASCII characters). X11 works by being asked for a font specification and coming up with its idea of a close match. For text (as distinct from the symbols used by plotmath), the specification is the first element of the option "X11fonts" which defaults to

If you are using a single-byte encoding, for example ISO 8859-2 in Eastern Europe or KOI8-R in Russian, use xlsfonts to find an appropriate family of fonts in your encoding (the last field in the listing). If you find none, it is likely that you need to install further font packages, such as ‘xorg-x11-fonts-ISO8859-2-75dpi’ and ‘xorg-x11-fonts-cyrillic’ shown in the listing above.

Multi-byte encodings (most commonly UTF-8) are even more complicated. There are few fonts in ‘iso10646-1’, the Unicode encoding, and they only contain a subset of the available glyphs (and are often fixed-width designed for use in terminals). In such locales fontsets are used, made up of fonts encoded in other encodings. If the locale you are using has an entry in the ‘XLC_LOCALE’ directory (typically /usr/share/X11/locale, it is likely that all you need to do is to pick a suitable font specification that has fonts in the encodings specified there. If not, you may have to get hold of a suitable locale entry for X11. This may mean that, for example, Japanese text can be displayed when running in ‘ja_JP.UTF-8’ but not when running in ‘en_GB.UTF-8’ on the same machine (although on some systems many UTF-8 X11 locales are aliased to ‘en_US.UTF-8’ which covers several character sets, e.g. ISO 8859-1 (Western European), JISX0208 (Kanji), KSC5601 (Korean), GB2312 (Chinese Han) and JISX0201 (Kana)).

On some systems scalable fonts are available covering a wide range of glyphs. One source is TrueType/OpenType fonts, and these can provide high coverage. Another is Type 1 fonts: the URW set of Type 1 fonts provides standard typefaces such as Helvetica with a larger coverage of Unicode glyphs than the standard X11 bitmaps, including Cyrillic. These are generally not part of the default install, and the X server may need to be configured to use them. They might be under the X11 fonts directory or elsewhere, for example,

C.2 Linux

Linux is the main development platform for R, so compilation from the sources is normally straightforward with the standard compilers.

Remember that some package management systems (such as RPM and deb) make a distinction between the user version of a package and the developer version. The latter usually has the same name but with the extension ‘-devel’ or ‘-dev’: you need both versions installed. So please check the configure output to see if the expected features are detected: if for example ‘readline’ is missing add the developer package. (On most systems you will also need ‘ncurses’ and its developer package, although these should be dependencies of the ‘readline’ package(s).)

When R has been installed from a binary distribution there are sometimes problems with missing components such as the FORTRAN compiler. Searching the ‘R-help’ archives will normally reveal what is needed.

It seems that ‘ix86’ Linux accepts non-PIC code in shared libraries, but this is not necessarily so on other platforms, in particular on 64-bit CPUs such as ‘x86_64’. So care can be needed with BLAS libraries and when building R as a shared library to ensure that position-independent code is used in any static libraries (such as the Tcl/Tk libraries, libpng, libjpeg and zlib) which might be linked against. Fortunately these are normally built as shared libraries with the exception of the ATLAS BLAS libraries.

The default optimization settings chosen for CFLAGS etc are conservative. It is likely that using -mtune will result in significant performance improvements on recent CPUs (especially for ‘ix86’): one possibility is to add -mtune=native for the best possible performance on the machine on which R is being installed: if the compilation is for a site-wide installation, it may still be desirable to use something like -mtume=core2.³⁹ It is also possible to increase the optimization levels to -O3: however for many versions of the compilers this has caused problems in at least one CRAN package.

is appropriate since most (but not all) software installs its 64-bit libraries in /usr/local/lib64. To build a 32-bit version of R on ‘x86_64’ with Fedora 16 we used

Note the use of ‘LIBnn’: ‘x86_64’ Fedora installs its 64-bit software in /usr/lib64 and 32-bit software in /usr/lib. Linking will skip over inappropriate binaries, but for example the 32-bit Tcl/Tk configure scripts are in /usr/lib. It may also be necessary to set the pkg-config path, e.g. by

64-bit versions of Linux are built with support for files > 2Gb, and 32-bit versions will be if possible unless --disable-largefile is specified.

To build a 64-bit version of R on ‘ppc64’ (also known as ‘powerpc64’) with gcc 4.1.1, Ei-ji Nakama used

the additional flags being needed to resolve problems linking against libnmath.a and when linking R as a shared library.

C.2.1 Clang

R has been built with Linux ‘ix86’ and ‘x86_64’ C and C++ compilers (http://clang.llvm.org, versions 2.9 and 3.0) based on the Clang front-ends, invoked by CC=clang CXX=clang++, together with gfortran. These take very similar options to the corresponding GCC compilers.

C.2.2 Intel compilers

Intel compilers have been used under ‘ix86’ and ‘x86_64’ Linux. Brian Ripley used version 9.0 of the compilers for ‘x86_64’ on Fedora Core 5 with

configure will add ‘-c99’ to CC for C99-compliance. This causes warnings with icc 10 and later, so use CC="icc -std=c99" there. The flag -wd188 suppresses a large number of warnings about the enumeration type ‘Rboolean’. Because the Intel C compiler sets ‘__GNUC__’ without complete emulation of gcc, we suggest adding CPPFLAGS=-no-gcc.

To maintain correct IEC 60559 arithmetic you most likely need add flags to CFLAGS, FFLAGS and CXXFLAGS such as -mp (shown above) or -fp-model precise -fp-model source, depending on the compiler version.

C.2.3 Oracle Solaris Studio compilers

-m64 could be added, but was the default. Do not use -fast: see the warnings under Solaris. (The C++ options are also explained under Solaris.)

Others have found on at least some versions of ‘ix86’ Linux that the configure flag --disable-largefile was needed (since glob.h on that platform presumed gcc was being used).

C.3 FreeBSD

Rainer Hurling has reported success on ‘amd64’ FreeBSD 9.0 (and on earlier versions in the past), and Brian Ripley tested ‘amd64’ FreeBSD 8.2. Since Darwin (the base OS of (Mac) OS X) is based on FreeBSD we find testing on Darwin tends to pick up most potential problems on FreeBSD. However, FreeBSD lacks adequate collation support for multi-byte locales (but a port of ICU is available), and does not yet implement C99 complex math functions (for which R’s substitutes are used).

The native BSD make suffices to build R but a number of packages require GNU make, despite the recommendations of the “Writing R Extensions” manual. (The BSD version is bsdmake on Darwin.)

The simplest way to get the additional software needed to build R is to install a pre-compiled version first, e.g. by

(on the system this was tested on, this installed Tcl, Tk, blas, lapack and gcc-4.6.2 which includes gfortran46). A listing of dependencies (not necessarily for current R) can be found at http://www.freebsd.org/ports/lang.html: you will however also need a TeX system⁴⁰ to build the manuals.

There are also FreeBSD packages for a small eclectic collection of CRAN packages.

C.4 (Mac) OS X

You can build R as a Unix application on OS X using the Apple Developer Tools (‘Xcode’) and a version of gfortran. (Recent versions of Xcode need ‘Command Line Tools for Xcode’.) You may also need to install an X sub-system or configure with --without-x. The X window manager is part of the standard OS X distribution. You will also need a version of gfortran and libreadline (or configure with --without-readline).

For more information on how to find these tools please read the R for Mac OS X FAQ.

The vecLib library in the Accelerate framework can be used via the configuration options

to provide higher-performance versions of the BLAS and LAPACK routines. It may also be necessary to include -D__ACCELERATE__ in CFLAGS, and omitting --with-lapack may be necessary, especially for Snow Leopard.

C.4.1 32-bit builds

It is safest to tell the compilers explicitly to compile for 32-bit code by setting

C.4.2 64-bit builds

64-bit builds are supported on 10.5.x (Leopard) and later. All that is needed is to select suitable compiler options, e.g.

C.4.3 Snow Leopard

A quirk on Snow Leopard is that the X11 libraries are not in the default linking path, so something like ‘LIBS=-L/usr/X11/lib’ may be required (or you can use the configure options --x-includes=/usr/X11/include --x-libraries=/usr/X11/lib.).

So for a 64-bit build of R you need a file config.site in the top-level build directory containing

C.4.4 Lion

With Xcode 4.2 and later you need to install a package named like http://r.research.att.com/tools/gcc-42-5666.3-darwin11.pkg to provide compilers named gcc-4.2, g++-4.2 and gfortran-4.2. These default to 64-bit, so for a 64-bit build config.site in the top-level build directory should contain

It is also possible to build R using Apple’s C/C++ compilers supplied with Xcode, but these do need to be supplemented by a Fortran compiler (such as gfortran-4.2). /usr/bin/gcc is a link to llvm-gcc, an LLVM-based compiler with a gcc 4.2.1 front end, and clang can also be used (and clang++ for C++).

C.4.5 Frameworks

The second line of options is only needed if you want to build R for use with R.app Console, and imply --enable-R-shlib to build R as a shared/dynamic library. These options configure R to be built and installed as a framework called R.framework. The default installation path for R.framework is /Library/Frameworks but this can be changed at configure time by specifying the flag --enable-R-framework[=DIR] or at install time as

Note that building the R.app GUI console is a separate project: see R for Mac OS X FAQ for details.

C.5 Solaris

R has been built successfully on Solaris 10 (both Sparc and ‘x86’) using the (zero cost) Oracle Solaris Studio compilers: there has been some success with gcc 4/gfortran. Sun packages for R used to be available from http://www.sunfreeware.com/ for both 32-bit architectures, but recently have often been many versions old. (Recent Sun machines are AMD Opterons or Intel Xeons (‘amd64’) rather than ‘x86’, but 32-bit ‘x86’ executables are the default.)

There have been no reports on Solaris 11. Solaris 9 and earlier are now so old that it is unlikely that R is still used with them, and they will not be considered here.

The Solaris versions of several of the tools needed to build R (e.g. make, ar and ld) are in /usr/ccs/bin, so if using those tools ensure this is in your path. A version of the preferred GNU tar is (if installed) in /usr/sfw/bin, as sometimes are tools like makeinfo. It may be necessary to avoid the tools in /usr/ucb: POSIX-compliant versions of some tools can be found in /usr/xpg4/bin and /usr/xpg6/bin.

A large selection of Open Source software can be installed from http://www.opencsw.org via pkg-get, by default installed under /opt/csw.

You will need GNU libiconv and readline: the Solaris version of iconv is not sufficiently powerful.

The native make suffices to build R but a small number of packages require GNU make (some without good reason and without declaring it as ‘SystemRequirements’ in the DESCRIPTION file).

Some people have reported that the Solaris libintl needs to be avoided, for example by using --disable-nls or --with-included-gettext or using libintl from OpenCSW.

When using the Oracle compilers⁴¹ do not specify -fast, as this disables IEEE arithmetic and make check will fail.

For the Solaris Studio compilers a little juggling of paths was needed to ensure GNU libiconv (in /usr/local) was used rather than the Solaris iconv:

For a 64-bit target add -m64 to the compiler macros and use something like LDFLAGS=-L/usr/local/lib/sparcv9 or LDFLAGS=-L/usr/local/lib/amd64 as appropriate. It will also be necessary to point pkg-config at the 64-bit directories, e.g. one of

(and possibly other Fortran libraries, but this suffices for the packages currently on CRAN).

Currently ‘amd64’ and ‘sparcv9’ builds work out-of-the-box with Sun Studio 12u1 but not Solaris Studio 12.2 and later: libRblas.so and lapack.so are generated with code that causes relocation errors (which is being linked in from the Fortran libraries). This means that building R as a shared library may be impossible with Solaris Studio >= 12.2. For a standard build the trick seems to be to manually set FLIBS to avoid the troublesome libraries. For example, on ‘amd64’ set in config.site something like

By default the Solaris Studio compilers do not by default conform to the C99 standard (appendix F 8.9) on the return values of functions such as log: use -xlibmieee to ensure this.

You can target specific Sparc architectures for (slightly) higher performance: -xtarget=native (in CFLAGS etc) tunes the compilation to the current machine.

Using -xlibmil in CFLAGS and -xlibmil in FFLAGS allows more system mathematical functions to be inlined.

but the use of -nofstore can be less numerically stable, and some packages (notably mgcv on ‘x86’) failed to compile at higher optimization levels with version 12.3.

The Solaris Studio compilers provide several implementations of the C++ standard which select both the set of headers and a C++ runtime library. These are selected by the -library flag, which as it is needed for both compiling and linking is best specified as part of the compiler. The examples above use ‘stlport4’, currently the most modern of the options: the default (but still needed to be specified as it is needed for linking) is ‘Cstd’: see http://developers.sun.com/solaris/articles/cmp_stlport_libCstd.html. Note though that most external Solaris C++ libraries will have been built with ‘Cstd’ and so an R package using such libraries also needs to be. Occasionally the flag -library=stlport4,Crun has been needed.

Several CRAN packages using C++ need the more liberal interpretation given by adding

The performance library sunperf is available for use with the Solaris Studio compilers. If selected as a BLAS, it must also be selected as LAPACK via (for Solaris Studio 12.2)

This has often given test failures in the past, in several different places. At the time of writing it fails in tests/reg-BLAS.R, and on some builds, including for ‘amd64’, it fails in example(eigen).

C.5.1 Using gcc

If using gcc, ensure that the compiler was compiled for the version of Solaris in use. (This can be ascertained from

gcc
-v

.) gcc makes modified versions of some header files, and several reports of problems were due to using gcc compiled on one version of Solaris on a later version.

The notes here are for gcc set up to use the Solaris linker: it can also be set up to use GNU ld, but that has not been tested.

Note that paths such as /opt/csw/gcc4/lib/sparcv9 may need to be in the LD_LIBRARY_PATH during configuration.

The compilation can be tuned to a particular cpu: the CRAN check system uses -mtune=niagara2.

(-L/opt/csw/lib is needed since TexLive 2011 was built using 32-bit gcc, and we need /opt/csw/lib in R_LD_LIBRARY_PATH.)

C.6 AIX

We no longer support AIX prior to 4.2, and configure will throw an error on such systems.

Ei-ji Nakama was able to build under AIX 5.2 on ‘powerpc’ with GCC 4.0.3 in several configurations. 32-bit versions could be configured with --without-iconv as well as --enable-R-shlib. For 64-bit versions he used

Some systems have f95 as an IBM compiler that does not by default accept FORTRAN 77. It needs the flag -qfixed=72, or to be invoked as xlf_r.

The AIX native iconv does not support encodings ‘latin1’ nor ‘""’ and so cannot be used. (As far as we know GNU libiconv could be installed.)

On one AIX 6.x system it was necessary to use R_SHELL to set the default shell to be Bash rather than Zsh.

Kurt Hornik and Stefan Theussl at WU (Wirtschaftsuniversität Wien) successfully built R on a ‘powerpc’ (8-CPU Power6 system) running AIX 6.1, configuring with or without --enable-R-shlib (Ei-ji Nakama’s support is gratefully acknowledged).

It helps to describe the WU build environment first. A small part of the software needed to build R and/or install packages is available directly from the AIX Installation DVDs, e.g., Java 6, X11, and Perl. Additional open source software (OSS) is packaged for AIX in .rpm files and available from both IBM’s “AIX Toolbox for Linux Applications” (http://www-03.ibm.com/systems/power/software/aix/linux/) and http://www.oss4aix.org/download/. The latter website typically offers more recent versions of the available OSS. All tools needed and libraries downloaded from these repositories (e.g., GCC, Make, libreadline, etc.) are typically installed to /opt/freeware, hence corresponding executables are found in /opt/freeware/bin which thus needs to be in PATH for using these tools. As on other Unix systems one needs GNU libiconv as the AIX version of iconv is not sufficiently powerful. Additionally, for proper Unicode compatibility one should install the corresponding package from the ICU project (http://www.icu-project.org/download/), which offers pre-compiled binaries for various platforms which in case of AIX can be installed via unpacking the tarball to the root file system. For full LaTeX support one can install the TeX Live DVD distribution (http://www.tug.org/texlive/): it is recommended to update the distribution using the tlmgr update manager. For 64-bit R builds supporting Tcl/Tk this needs to installed from the sources as available pre-compiled binaries supply only 32-bit shared objects.

The recent WU testing was done using compilers from both the GNU Compiler Collection (version 4.2.4) which is available from one of the above OSS repositories, and the IBM C/C++ (XL C/C++ 10.01) as well as FORTRAN (XL Fortran 12.01) compilers (http://www14.software.ibm.com/webapp/download/byproduct.jsp#X).

for the IBM XL compilers. For the latter, it is important to note that the decision for generating 32-bit or 64-bit code is done by setting the OBJECT_MODE environment variable appropriately (recommended) or using an additional compiler flag (-q32 or -q64). By default the IBM XL compilers produce 32 bit code. Thus, to build R with 64-bit support one needs to either export OBJECT_MODE=64 in the environment or, alternatively, use the -q64 compiler options.

It is strongly recommended to install Bash and use it as the configure shell, e.g., via setting CONFIG_SHELL=/usr/bin/bash in the environment, and to use GNU Make (e.g., via (MAKE=/opt/freeware/bin/make).

Further installation instructions to set up a proper R development environment can be found in the “R on AIX” project on R-Forge (http://R-Forge.R-project.org/projects/aix/).

C.7 Cygwin

The Cygwin emulation layer on Windows can be treated as a Unix-alike OS. This is unsupported, but experiments have been conducted and a few workarounds added. R requires C99 complex type support, which is available as from Cygwin 1.7.8 (March 2011). However, the (new) implementation of cacos gives incorrect results, so we undefine HAVE_CACOS in src/main/complex.c on that platform.

Many versions of Cygwin during 2011 were unable to build R: 1.7.9-1 with GCC 4.5.3-3 in November 2011 was able to do so.

Enabling NLS does work if required, although adding --with-included-gettext is preferable. You will see many warnings about the use of auto-import. Setting ‘FLIBS’ explicitly seems needed currently as the auto-detection gives an incorrect values.

You will need the tetex-extra Cygwin package to build NEWS.pdf and the vignettes.

Note that this gives you a command-line application using readline for command editing. The ‘X11’ graphics device will work if a suitable X server is running, and the standard Unix-alike ways of installing source packages work. There was a bug in the /usr/lib/tkConfig.sh script in the version we looked at, which needs to have

The overhead of using shell scripts makes this noticeably slower than a native build of R on Windows.

Even when R can be built, not all the tests passed: there were incorrect results from wide-character regular expressions code and from sourcing CR-delimited files.

C.8 New platforms

There are a number of sources of problems when installing R on a new hardware/OS platform. These include

Floating Point Arithmetic: R requires arithmetic compliant with IEC 60559, also known as IEEE 754. This mandates the use of plus and minus infinity and NaN (not a number) as well as specific details of rounding. Although almost all current FPUs can support this, selecting such support can be a pain. The problem is that there is no agreement on how to set the signalling behaviour; Sun/Sparc, SGI/IRIX and ‘ix86’ Linux require no special action, FreeBSD requires a call to (the macro) fpsetmask(0) and OSF1 requires that computation be done with a -ieee_with_inexact flag etc. On a new platform you must find out the magic recipe and add some code to make it work. This can often be done via the file config.site which resides in the top level directory.

Beware of using high levels of optimization, at least initially. On many compilers these reduce the degree of compliance to the IEEE model. For example, using -fast on the Solaris Studio compilers has caused R’s NaN to be set incorrectly.

Shared Objects: There seems to be very little agreement across platforms on what needs to be done to build shared objects. there are many different combinations of flags for the compilers and loaders. GNU libtool cannot be used (yet), as it currently does not fully support FORTRAN: one would need a shell wrapper for this). The technique we use is to first interrogate the X window system about what it does (using xmkmf), and then override this in situations where we know better (for tools from the GNU Compiler Collection and/or platforms we know about). This typically works, but you may have to manually override the results. Scanning the manual entries for cc and ld usually reveals the correct incantation. Once you know the recipe you can modify the file config.site (following the instructions therein) so that the build will use these options.

It seems that gcc 3.4.x and later on ‘ix86’ Linux defeat attempts by the LAPACK code to avoid computations entirely in extended-precision registers, so file src/modules/lapack/dlamc.f may need to be compiled without optimization. Set the configure variable SAFE_FFLAGS to the flags to be used for this file. If configure detects GNU FORTRAN it adds flag -ffloat-store to FFLAGS. (Other settings are needed when using icc on ‘ix86’ Linux, for example. Using -mpc64 is preferable on more recent GCC compilers.)

If you do manage to get R running on a new platform please let us know about it so we can modify the configuration procedures to include that platform.

If you are having trouble getting R to work on your platform please feel free to use the ‘R-devel’ mailing list to ask questions. We have had a fair amount of practice at porting R to new platforms ...

Appendix D The Windows toolset

If you want to build R or add-on packages from source in Windows, you will need to collect, install and test an extensive set of tools. See http://cran.r-project.org/bin/windows/Rtools/ for the current locations and other updates to these instructions. (Most Windows users will not need to build add-on packages from source; see Add-on packages for details.)

We have found that the build process for R is quite sensitive to the choice of tools: please follow our instructions exactly, even to the choice of particular versions of the tools.⁴³ The build process for add-on packages is somewhat more forgiving, but we recommend using the exact toolset at first, and only substituting other tools once you are familiar with the process.

This appendix contains a lot of prescriptive comments. They are here as a result of bitter experience. Please do not report problems to the R mailing lists unless you have followed all the prescriptions.

We have collected most of the necessary tools (unfortunately not all, due to license or size limitations) into an executable installer named⁴⁴ Rtools215.exe, available from http://cran.r-project.org/bin/windows/Rtools/. You should download and run it, choosing the default “Package authoring installation” to build add-on packages, or the “full installation” if you intend to build R.

You will need the following items to build R and packages. See the subsections below for detailed descriptions.

For installing simple source packages containing data or R source but no compiled code, none of these are needed. Perl is no longer needed to build R nor to install nor develop source packages.

A complete build of R including PDF manuals, and producing the installer will also need the following:

It is important to set your PATH properly. The installer Rtools*.exe optionally sets the path to components that it installs.

Your PATH may include . first, then the bin directories of the tools, the compiler toolchain and LaTeX. Do not use filepaths containing spaces: you can always use the short forms (found by dir /x at the Windows command line). Network shares (with paths starting \\) are not supported.

It is essential that the directory containing the command line tools comes first or second in the path: there are typically like-named tools⁴⁵ in other directories, and they will not work. The ordering of the other directories is less important, but if in doubt, use the order above.

Our toolset contains copies of Cygwin DLLs that may conflict with other ones on your system if both are in the path at once. The normal recommendation is to delete the older ones; however, at one time we found our tools did not work with a newer version of the Cygwin DLLs, so it may be safest not to have any other version of the Cygwin DLLs in your path.

D.1 LaTeX

The ‘MiKTeX’ (http://www.miktex.org/) distribution of LaTeX includes a suitable port of pdftex. The ‘basic’ version of ‘MiKTeX’ almost suffices (the grid vignettes need fancyvrb.sty), but it will install the 15Mb ‘lm’ package if allowed to (although that is not actually used). The Rtools*.exe installer does not include any version of LaTeX.

Please read Making the manuals about how to make refman.pdf and set the environment variable R_RD4PDF suitably; ensure you have the required fonts installed or that ‘MiKTeX’ is set up to install LaTeX on first use.

D.2 The Inno Setup installer

To make the installer package (R-2.15.1-win.exe) we currently require Inno Setup 5.3.7 or later (including 5.4.x) from http://jrsoftware.org/. We use the Unicode version and recommend that version be used. This is not included in Rtools*.exe.

Copy file src/gnuwin32/MkRules.dist to src/gnuwin32/MkRules.local and edit it to set ISDIR to the location where Inno Setup was installed.

D.3 The command line tools

If you choose to install these yourself, you will need suitable versions of at least basename, cat, cmp, comm, cp, cut, date, diff, du, echo, expr, gzip, ls, make, makeinfo, mkdir, mv, rm, rsync, sed, sh, sort, tar, texindex, touch and uniq; we use those from the Cygwin distribution (http://www.cygwin.com/) or compiled from the sources. You will also need zip and unzip from the Info-ZIP project (http://www.info-zip.org/). All of these tools are in Rtools*.exe.

Beware: ‘Native’ ports of make are not suitable (including those called ‘MinGW make’ at the MinGW SourceForge site and mingw32-make in some MinGW-w64 distributions). There were also problems with other versions of the Cygwin tools and DLLs. To avoid frustration, please use our tool set, and make sure it is at the front of your path (including before the Windows system directories). If you are using a Windows shell, type PATH at the prompt to find out.

You may need to set the environment variable CYGWIN to a value including ‘nodosfilewarning’ to suppress messages about Windows-style paths.

D.4 The MinGW-w64 toolchain

Technically you need more than just a compiler so the set of tools is referred to as a ‘toolchain’.

The released version of R 2.15.0 will be built with a different toolchain from R 2.12.0 to 2.14.1. The preferred toolchain is part of Rtools215.exe: this uses a beta version of gcc 4.6.3 and version 2.0.1 of the MinGW-w64 project’s runtime.

This toolchain uses multilib: that is there is a single front-end such as gcc.exe for each of the compilers and 32-bit (the default) and 64-bit compilation are selected by the flags⁴⁶ -m32 and -m64 respectively. The tools are all 32-bit Windows executables and should be able to run on any current version of Windows—however you do need a 64-bit version of Windows to build 64-bit R as the build process runs R.

To select a 32-bit or 64-bit build of R, set the options in MkRules.local appropriately (following the comments in the file).

Some external software libraries will need to be re-compiled under the new toolchain: especially those providing a C++ interface. Many of those used by CRAN packages are available from http://www.stats.ox.ac.uk/pub/Rtools/multilib/. Users developing packages with Rcpp need to ensure that they use a version built with exactly the same toolchain as their package: the recommendation is to build Rcpp from its sources yourself.

There is support for OpenMP and pthreads in this toolchain. As the performance of OpenMP on Windows is poor for small tasks, it is not used for R itself.

D.5 Useful additional programs

The process of making the installer will make use of qpdf to compact some of the package vignettes, if it is available. Windows binaries of qpdf are available from http://sourceforge.net/projects/qpdf/files/. Set the path to the qpdf installation in file MkRules.local.

There is a version of the file command that identifies the type of files, and is used by Rcmd check if available. The binary distribution is included in Rtools215.exe.

The file xzutils.zip contains the program xz which can be used to (de)compress files with that form of compression.

Function and variable index

Concept index

Environment variable index

• Obtaining pqR and R
• Installing R under Unix-alikes
• Installing R under Windows
• Installing R under (Mac) OS X
• Running R
• Add-on packages
• Internationalization
• Choosing between 32- and 64-bit builds
• The standalone Rmath library
• Essential and useful other programs under a Unix-alike
• Configuration on a Unix-alike
• Platform notes
• The Windows toolset
• Function and variable index
• Concept index
• Environment variable index

• Simple compilation
• Help options
• Making the manuals
• Installation
• Uninstallation
• Sub-architectures
• Other Options
• Stack growth direction
• Testing a Unix-alike Installation

• Getting the tools
• Getting the source files
• Building the core files
• Building the bitmap files
• Building the cairo devices files
• Checking the build
• Building the manuals
• Building the Inno Setup installer
• Building the MSI installer
• Cross-building on Linux
• 64-bit Windows builds

• Default packages
• Managing libraries
• Installing packages
• Updating packages
• Removing packages
• Setting up a package repository
• Checking installed source packages

• Windows packages
• OS X packages
• Customizing package compilation
• Multiple sub-architectures
• Byte-compilation

• Getting and unpacking the sources
• Getting patched and development versions

• Locales under Linux
• Locales under Windows
• Locales under OS X

• Essential programs and libraries
• Useful libraries and programs
• Linear algebra

• Configuration options
• Compressed and uncompressed pointers
• Helper threads and task merging
• Internationalization support
• Configuration variables
• Setting the shell
• Using make
• Using FORTRAN
• Compile and load flags

• Setting paper size
• Setting the browsers
• Compilation flags
• Making manuals

• X11 issues
• Linux
• FreeBSD
• Mac OS X
• Solaris
• AIX
• Cygwin
• New platforms

• Clang
• Intel compilers
• Oracle Solaris Studio compilers

• 32-bit builds
• 64-bit builds
• Snow Leopard
• Lion
• Frameworks

• LaTeX
• The Inno Setup installer
• The command line tools
• The MinGW-w64 toolchain
• Useful additional programs

	Index Entry	Section

C
	`configure`:	Simple compilation
	`configure`:	Simple compilation
	`configure`:	Installation
	`configure`:	Installation
	`configure`:	Configuration variables
	`configure`:	Using make

I
	`install.packages`:	Installing packages

M
	`make`:	Using make

R
	`remove.packages`:	Removing packages
	`R_HOME`:	Simple compilation

U
	`update.packages`:	Updating packages

	Index Entry	Section

A
	AIX:	AIX

B
	BLAS library:	Linear algebra
	BLAS library:	Using FORTRAN
	BLAS library:	Mac OS X
	BLAS library:	Solaris

F
	FORTRAN:	Using FORTRAN
	FreeBSD:	FreeBSD

I
	Installation:	Installation
	Installing under Unix-alikes:	Installing R under Unix-alikes
	Installing under Windows:	Installing R under Windows
	Internationalization:	Internationalization

L
	LAPACK library:	LAPACK
	LAPACK library:	Mac OS X
	LAPACK library:	Solaris
	Libraries:	Add-on packages
	Libraries, managing:	Managing libraries
	Libraries, site:	Managing libraries
	Libraries, user:	Managing libraries
	Linux:	Installing R under Unix-alikes
	Linux:	Linux
	Locale:	Internationalization
	Locale:	Locales
	Localization:	Internationalization

M
	Manuals:	Making the manuals
	Manuals, installing:	Installation

O
	Obtaining pqR and R:	Obtaining pqR and R
	OS X:	Installing R under Unix-alikes
	OS X:	Installing R under (Mac) OS X
	OS X:	Mac OS X

P
	Packages:	Add-on packages
	Packages, default:	Default packages
	Packages, installing:	Installing packages
	Packages, removing:	Removing packages
	Packages, updating:	Updating packages

R
	Rbitmap.dll:	Building the bitmap files
	Repositories:	Setting up a package repository

S
	Site libraries:	Managing libraries
	Solaris:	Solaris
	Sources for R:	Getting and unpacking the sources
	Subversion:	Using Subversion and rsync
	Subversion:	Essential programs and libraries

U
	User libraries:	Managing libraries

V
	Vignettes:	Essential programs and libraries

W
	winCairo.dll:	Building the cairo devices files

	Index Entry	Section

B
	`BLAS_LIBS`:	BLAS

C
	`CC`:	Using FORTRAN
	`CONFIG_SITE`:	Configuration variables
	`CPP`:	Using FORTRAN
	`CYGWIN`:	The command line tools

D
	`DESTDIR`:	Installation
	`DESTDIR`:	Unix-alike standalone

F
	`F2C`:	Using FORTRAN
	`F2CLIBS`:	Using FORTRAN
	`FPICFLAGS`:	Using FORTRAN

J
	`JAVA_HOME`:	Java support

L
	`LANG`:	Localization of messages
	`LANGUAGE`:	Localization of messages
	`LANGUAGE`:	Localization of messages
	`LAPACK_LIBS`:	LAPACK
	`LC_ALL`:	Localization of messages
	`LC_COLLATE`:	Testing a Unix-alike Installation
	`LC_MESSAGES`:	Localization of messages
	`LD_LIBRARY_PATH`:	Unix-alike standalone
	`LD_LIBRARY_PATH`:	ACML
	`LD_LIBRARY_PATH`:	Using FORTRAN
	`LD_LIBRARY_PATH`:	Compile and load flags
	`LD_LIBRARY_PATH`:	Using gcc

O
	`OBJECT_MODE`:	AIX

P
	`PAPERSIZE`:	Setting paper size
	`PATH`:	Essential programs and libraries
	`PATH`:	Using FORTRAN
	`PATH`:	AIX
	`PATH`:	The Windows toolset

R
	`R_ARCH`:	Sub-architectures
	`R_ARCH`:	Sub-architectures
	`R_BROWSER`:	Setting the browsers
	`R_DEFAULT_PACKAGES`:	Default packages
	`R_DISABLE_HTTPD`:	Help options
	`R_GSCMD`:	Useful libraries and programs
	`R_INSTALL_TAR`:	Windows packages
	`R_JAVA_LD_LIBRARY_PATH`:	Java support
	`R_JAVA_LD_LIBRARY_PATH`:	Java support
	`R_LIBS`:	Add-on packages
	`R_LIBS_SITE`:	Managing libraries
	`R_LIBS_USER`:	Managing libraries
	`R_PAPERSIZE`:	Making the manuals
	`R_PAPERSIZE`:	Running R
	`R_PAPERSIZE`:	Setting paper size
	`R_PAPERSIZE`:	Making manuals
	`R_PDFVIEWER`:	Setting the browsers
	`R_RD4PDF`:	Making the manuals
	`R_RD4PDF`:	Making manuals
	`R_RD4PDF`:	LaTeX
	`R_SHELL`:	AIX
	`R_USER`:	Running R

T
	`TAR`:	Essential programs and libraries
	`TAR_OPTIONS`:	Getting and unpacking the sources
	`TAR_OPTIONS`:	Getting the source files
	`TEMP`:	Running R
	`TMP`:	Running R
	`TMPDIR`:	Simple compilation
	`TMPDIR`:	Building the core files
	`TMPDIR`:	Running R
	`TMPDIR`:	Running R
	`TMPDIR`:	Installing packages

R Installation and Administration - with modifications for pqR

Table of Contents

1 Obtaining pqR and R