R Installation and Administration

Sources, binaries and documentation for R can be obtained via CRAN, the "Comprehensive R Archive Network". See the file RESOURCES in the R distribution for information on CRAN.

1.1 Getting and unpacking the sources

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

on systems that have GNU tar installed. On other systems you need at least to have the gzip program installed. Then you can use

If you need to transport the sources on floppy disks, you can download the R-x.y.z.tgz-split.* files and paste them together at the destination with (Unix)

and proceed as above. 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).

1.2 Using rsync

to create a copy of the source tree specified by module in the subdirectory R of the current directory, where module specifies one of the four existing flavors of the R sources, and can be one of r-release (current released version), r-patched (patched released version), and r-devel (development version). (These flavors are described in the R FAQ, http://www.ci.tuwien.ac.at/~hornik/R/.) The rsync trees are created directly from the master CVS archive and are updated hourly. The -C option in the rsync command is to cause it to skip the CVS directories. Further information on rsync is available at http://rsync.samba.org/rsync/.

2 Installing R under Unix

R will configure and build under a number of common Unix platforms including i386-freebsd, cpu-linux-gnu for the i386, alpha, arm, hppa, ia64, m68k, powerpc, and sparc CPUs (see e.g. http://buildd.debian.org/build.php?&pkg=r-base), i386-sun-solaris, powerpc-apple-darwin, mips-sgi-irix, alpha-dec-osf4, rs6000-ibm-aix, hppa-hp-hpux, and sparc-sun-solaris.

In addition, binary distributions are available for most common Linux distributions, and for MacOS X (Darwin) with X11. 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

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. Issue the following commands:

Failures are not necessarily problems as they might be caused by missing functionality, but you should look carefully at any reported discrepancies. To re-run the tests you would need

If these commands execute successfully, the R binary will be copied to the R_HOME/bin directory. In addition, a shell-script front-end called R will be created and copied to the same directory. 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". (You may need GNU make to allow this.)

Make will also build plain text help pages as well as HTML and LaTeX versions of the R object documentation (the three kinds can also be generated separately using make help, make html and make latex). Note that you need Perl version 5: if this is not available on your system, you can obtain PDF versions of the documentation files via CRAN.

Now rehash if necessary, type R, and read the R manuals and the R FAQ (files FAQ or doc/html/faq.html, or http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html which always has the latest version).

2.2 Making the manuals

You will not be able to build the info files unless you have makeinfo version 4 or later installed (and some Linux distributions have 3.12).

The DVI versions can be previewed and printed using standard programs such as xdvi and dvips. The PDF versions can be viewed using Acrobat Reader or (recent versions of) ghostscript: they have hyperlinks that can be followed in Acrobat Reader. The info files are suitable for reading online with Emacs or the standalone GNU Info.

2.3 Installation

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 executable 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 by using

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.

3 Installing R under Windows

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 95, 98, NT4, 2000, ME and XP (at least) on Intel and clones (but not on other platforms).

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

The simplest way is to use rw1081.exe or miniR.exe. Just double-click on the icon and follow the instructions. If you installed R this way you can uninstall it from the Control Panel.

3.1 Building from source

If you want to build this port from the sources, see the file src/gnuwin32/INSTALL in the source distribution. You will need to collect, install and test an extensive set of tools: see http://www.stats.ox.ac.uk/pub/Rtools/ for the current locations.

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 commands window at a directory whose path does not contain spaces, and run something like

For further details, including how to make the documentation and how to cross-compile, see src/gnuwin32/INSTALL.

4 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().

4.1 Installing packages

Packages may be distributed in source form or compiled binary form. Installing source packages requires that compilers and tools (including Perl 5.004 or later) 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 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.

The part -l /path/to/library can be omitted, in which case the first library in R_LIBS is used if set, otherwise the main library R_HOME/library is used. (R_LIBS is looked for in the environment: .Renviron is not read by R CMD.)

Alternatively, packages can be downloaded and installed from within R. First set the option CRAN to your nearest CRAN mirror, for example

Unless the library is specified (argument lib) the first library in the library search path is used.

What this does is different on Unix and Windows. On Unix it consults the list of available source packages on CRAN, downloads the latest version of the foo sources, and installs it (via

R
CMD INSTALL

). On Windows it looks at the list of binary versions of packages and downloads the latest version (if any).

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

4.2 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 CRAN option 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 CRAN.

An alternative way of 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 (CRAN, local archive, ...). The print and summary methods give an overview of installed and available packages, the upgrade method offers to fetch and install outdated packages. This allows R to fetch packages from several repositories and keep in sync with all of them, instead of only one CRAN mirror, and is intended to become the default package manager for future versions of R.

4.3 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.

Note: whereas it is currently possible to install package bundles, one cannot remove these as such--the packages contained in the bundle have to removed individually.

Appendix A Essential and useful other programs

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

You need a means of compiling C and FORTRAN 77 (see Using FORTRAN). Some add-on packages also need a C++ compiler.

Unless you do not want to view graphs on-screen you need X11 installed, including its headers and client libraries. (On RedHat Linux this means the XFree86-devel and XFree86-libs RPMs, for example.)

You will need Perl version 5.004 or later, available via http://www.perl.com/CPAN/, to build any of the on-line documentation.

You will not be able to build the info files unless you have makeinfo version 4 or later installed.

A.2 Useful libraries and programs

The command-line editing depends on the readline library available from any GNU mirror: you will need a fairly recent version.

The bitmapped graphics devices jpeg() and png() need the appropriate headers and libraries installed: jpeg (version 6b or later) or libpng (version 1.2.3 or later) and zlib (version 1.1.3 or later) respectively.

If you have them installed (including the appropriate headers), zlib, libbz2 and PCRE will be used: otherwise versions in the R sources will be compiled in.

A.2.1 Tcl/Tk

The tcltk package needs Tcl/Tk installed: the sources are available at http://www.scriptics.com/. 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.

Versions of Tcl/TK from 8.3 to 8.4.4 have been used successfully: 8.0 is no longer supported.

A.2.2 Linear algebra

The linear algebra routines in R can make use of enhanced BLAS (Basic Linear Algebra Subprograms, http://www.netlib.org/blas/faq.html) routines. Some are compiler-system-specific (libsunperf on Sun Sparc², libessl on IBM, vecLib on MacOS X) but ATLAS (http://math-atlas.sourceforge.net/) is a "tuned" BLAS that runs on a wide range of Unix-alike platforms. If no more specific library is found, a libblas library in the library path will be used. You can specify a specific BLAS library by the configuration option --with-blas and not to use an external BLAS library by --without-blas.

For systems with multiple processors it is possible to use a multi-threaded version of ATLAS. (Prior to R 1.8.0 this was not supported since SIGINT signals sent to the process and handled by the wrong thread could result in segfaults.) A remaining issue is that R profiling, which uses the SIGPROF signal, may cause problems. You may want to disable profiling if you use a multi-threaded version of ATLAS. You can use a multi-threaded ATLAS by specifying

Note that the BLAS library will be used for several add-on packages as well as for R itself. This means that it is better to use a shared BLAS library, as most of a static library will be compiled into the R executable and each BLAS-using package. In any case, the BLAS library must be usable with dynamically-loadable code.

You will need double-precision and double-complex versions of the BLAS, but not single-precision nor complex routines.

Provision is made for using an external LAPACK library, principally to cope with BLAS libraries which contain a copy of LAPACK (such as libsunperf on Solaris and vecLib on MacOS 10.2.2). 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. 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

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

(from the Debian -llapack which was current in late 2002). Other potential problems are incomplete versions of the libraries: for example libsunperf from Sun Forte 6.x was missing the entry point for DLANGE and vecLib has omitted the BLAS routine LSAME.

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

An ATLAS `tuned' BLAS can also be used on Windows: see src/gnuwin32/INSTALL for how to enable this when building from source, and R Windows FAQ for adding pre-compiled support to binary versions.

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

Appendix B Configuration on Unix

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 shared library, typically called libR.so, and to take considerably longer, so you probably only want this if you will be using an application which embeds R.

B.2 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 all the variables you might want to set) or on the command line as

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 and 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.

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

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 /usr/local/lib and /usr/local/include 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).

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

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.3 Using make

To compile R, you will most likely find it easiest to use GNU make. On Solaris 2.6/7/8 in particular, you need a version of GNU make different from 3.77; 3.79.1 works fine, as does the Sun make. The native make is 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 2.7/8 (but not earlier).

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.4 Using FORTRAN

To compile R, you need a FORTRAN compiler or f2c, the FORTRAN-to-C converter (http://www.netlib.org/f2c). The default is to search for g77, f77, xlf, frt, pgf77, fl32, af77, fort77, f90, xlf90, pgf90, epcf90, f95, fort, xlf95, lf95, g95, and fc (in that order)³, and then for f2c, and use whichever is found first; if none is found, R cannot be compiled. The search mechanism can be changed using the configure variables F77 and F2C which specify the commands that run the FORTRAN 77 compiler and FORTRAN-to-C converter, respectively. If F77 is given, it is used to compile FORTRAN; otherwise, if F2C is given, f2c is used even if a FORTRAN compiler would be be available. 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.

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 time⁴, but you may need to avoid compiler flags⁵ asserting FORTRAN 77 compliance.

If you use f2c you may 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.

B.5 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.

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.

B.6 Building the GNOME interface

This interface is experimental and incomplete. It provides a console and two graphics devices named gtk() and gnome(). The console offers a basic command line editing and history mechanism, along with tool and button bars that give a point-and-click interface to some R commands. Many of the features of the console are currently stubs. The gtk() graphics device is a port of the x11() device to GDK (the GIMP Drawing Kit). The gnome() device uses the GNOME canvas.

Due to its experimental nature, the GNOME interface for R will not be built automatically. You must specify it by running configure with the --with-gnome option. For example, you might run

but please check you have all the requirements first. You need at least the following libraries (or later) installed

It is preferable to have a complete installation of the GNOME desktop environment. If you use Linux, then this should be provided with your distribution. In addition, packaged binary distributions of GNOME are available from http://www.ximian.com for the most popular Linux distributions and for Solaris.

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. If you use a pre-packaged version of GNOME then you must have the developer versions of the above packages in order to compile the R-GNOME interface.

B.7 Platform notes

This section provides some notes on building R on different Unix-like 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.

B.7.1 Linux

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

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 package containing its headers.

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.

B.7.2 MacOS X

You can build R as a Unix application on MacOS X. You will need the DevTools, f2c or g77, and the dlcompat library. You will also need to install an X sub-system or configure with --without-x.

f2c, g77, the dlcompat library, and X server and support libraries are available from the Fink project (http://fink.sourceforge.net). At the time of writing f2c and g77 were not available as part of the Fink binary distribution and needed to be installed directly; for example for g77 use

The vecLib library of MacOS >= 10.2.2 can be used via the configuration options

to provide higher-performance versions of the BLAS and LAPACK routines. With gcc 3.1 that appears to be the only way to build R, as the Fortran support routines in libg2c cannot be linked into a dynmaic library. (We have had reports of success with pre-release versions of gcc 3.3.)

B.7.3 Solaris on Sparc

R has been built successfully on Solaris 8 aka Solaris 2.8 aka SunOS 5.8 using gcc/g77 and the SunPro WorkShop 6 (aka Forte 6) compilers and the `Sun ONE Studio 7 Compiler Suite' (aka Forte 7), and less regularly on Solaris 2.5.1, 2.6, 2.7 and 9. GNU make is needed prior to Solaris 2.7 for building other than in the source tree, and perhaps even then.

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.

gcc 3.2.1 and 3.2.2 generate incorrect code on 32-bit Solaris builds with optimization, but versions 3.1, 3.2, 3.2.3 and 3.3.x work correctly. At least files src/main/engine.c, src/main/graphics.c and src/modules/devX11.c are affected.

If using gcc, do 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 so (for example) gcc compiled under Solaris 2.6 will not compile R under Solaris 2.7. Also, do ensure that it was compiled for the assembler/loader in use. If you download gcc from http://www.sunfreeware.com then you need to download binutils too. To avoid all these pitfalls we strongly recommended you compile gcc from the sources yourself.

When using the SunPro compilers do not specify -fast, as this disables IEEE arithmetic and make check will fail. The maximal set of optimization options known to work is

We have found little performance difference between gcc and cc but considerable benefit from using a SunPro Fortran compiler: the gcc/f77 combination works well. For many C++ applications (e.g. package Matrix) Forte 7 requires -lCstd, which the configure script will add to SHLIB_CXXLDFLAGS if it identifies the compiler correctly.

To compile for a 64-bit target on Solaris (which needs an UltraSparc chip and for support to be enabled in the OS) with the Forte 6 and 7 compilers we used

Note that /usr/local/lib/sparcv9 will need to be in the LD_LIBRARY_PATH during configuration.

Note that using f95 allows the Sun performance library libsunperf to be selected: it will not work with f77, nor with g77. libsunperf contains both BLAS and LAPACK code, and --with-lapack is recommended for 32-bit builds using f95, but not for 64-bit builds where on our test system it failed in both Forte 6U1 and 7, albeit in different ways. Our experience has been that ATLAS's BLAS is faster than libsunperf, especially for complex numbers.

Some care is needed to ensure that libraries found by configure are compatible with the R executable and modules, as the testing process will not detect many of the possible problems. For 32-bit builds under cc the flag -dalign is needed for some of the Sun libraries: fortunately the equivalent flag for gcc, -mno-unaligned-doubles, is the default. In theory, libraries such as libpng, libjpeg, zlib and the ATLAS libraries need to be built with a pic or PIC flag, which could be a problem if static libraries are used. In practice this seems to give little problem for 32-bit builds.

For a 64-bit build, 64-bit libraries must be used. As the configuration process by default sets LDFLAGS to -L/usr/local/lib, you may need to set it to avoid finding 32-bit addons (as in the gcc -m64 example above).

B.7.4 HP-UX

R has been built successfully on HP-UX 10.2 and HP-UX 11.0 using both native compilers and gcc. However, 10.2 has not been tested since R 1.4.0. By default, R is configured to use gcc and g77 on HP-UX (if available). Some installations of g77 only install a static version of the g2c library that cannot be linked into a shared library since its files have not been compiled with the appropriate flag for producing position independent code (PIC). This will result in make failing with a linker error similar to

(+z and +Z are the PIC flags for the native compiler cc.) If this is the case you either need to modify your g77 installation or configure with

You may find that configure detects other libraries that R needs to use as shared libraries but are only available as static libraries. If you cannot install shared versions you will need to tell configure not to use these libraries, or make sure they are not in the library path. The symptom will the linker error shown in the last paragraph. Static libraries that might be found and would cause problems are

and bzip2 and pcre are problematic when building libR.so, only. These can be avoided by --without-bzlib and --without-pcre respectively.

Some versions of gcc may contain what appears to be a bug at the -O2 optimization level that causes

which will cause make check to fail. If this is the case, you should use CFLAGS to specify -O as the optimization level to use.

Some systems running HP-UX 11.0 may have a gcc that was installed under HP-UX 10.2. Between versions 10.2 and 11.0 HP-UX changed its support functions for IEEE arithmetic from the recommended functions of the IEEE standard to the ones specified in the C9x draft standard. In particular, this means that finite has been replaced by isfinite. A gcc configured for HP-UX 10.2 run on 11.0 will not find isfinite, and as a result configure does not recognize the machine as fully supporting IEEE arithmetic and does not define IEEE_754 when compiling C code. This results in a failure in

make
check

. The best solution is to install a properly configured gcc. An alternative work-around is to add -DIEEE_754 to the CFLAGS variable.

f90 insists on linking against a static libF90.a which typically resides in a non-standard directory (e.g., /opt/fortran90/lib). Hence, to use f90 one needs to add this directory to the linker path via the configure variable LDFLAGS (e.g.,

./configure F77=f90
LDFLAGS=/opt/fortran90/lib

B.7.5 IRIX

R has been built successfully on IRIX64 6.5 using gcc/f77 or cc/f77 for 32-bit executables and the native compilers for a 64-bit executable. The command

was used to create the 64-bit executable. It was necessary to explicitly omit Tcl/Tk because configure would find the 32-bit version but not detect that is was incompatible with a 64-bit build.

A 32-bit build using gcc/g77 passed

make
check

but failed make test-all-extras in the complex LAPACK tests.

B.7.6 Alpha/OSF1

R has been built successfully on an Alpha running OSF1 V4.0 using gcc/g77 and cc/f77. Mixing cc and g77 fails to configure. The configure option --without-blas was used since the native blas seems not to have been built with the flags needed to suppress SIGFPE's. Currently R does not set a signal handler for SIGFPE on platforms that support IEEE arithmetic, so these are fatal.

B.7.7 Alpha/FreeBSD

Attempts to build R on an Alpha with FreeBSD 4.3 have been only partly successful. Configuring with -mieee added to both CFLAGS and FFLAGS builds successfully, but tests fail with SIGFPE's. It would appear that -mieee only defers these rather than suppressing them entirely. Advice on how to complete this port would be greatly appreciated.

B.7.8 AIX

On AIX 4.3.3 and AIX 5.1, it was found that the use of "run time linking" (as opposed to normal AIX style linking) was required. For this, the R main program must be linked to the runtime linker with the -brtl linker option, and shareable objects must be enabled for runtime linking with the -G linker option. Without these options, the AIX linker will not automatically link to any shared object with a .so extension. Also, the R main program is unable to dynamically load modules (such as X11) with the dlopen call.

When setting MAIN_LDFLAGS and SHLIB_LDFLAGS accordingly, note that linker flags must be escaped using -Wl, if gcc is used for linking: use MAIN_LDFLAGS="-Wl,brtl" and SHLIB_LDFLAGS="-Wl,-G" in this case.

Harald Servat Gelabert <harald@cepba.upc.es> reported success building R 1.7.0 under AIX 5.1 with

but was unable to use the X libraries or the native BLAS (ESSL) and so used --without-x --without-blas.

Appendix C 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 supports the POSIX, SVID and IEEE models for floating point arithmetic. The POSIX and SVID models provide no problems. The IEEE model however 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 SunPro compilers causes R's NaN to be set incorrectly.

Shared Libraries: There seems to be very little agreement across platforms on what needs to be done to build shared libraries. 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 (and will most likely never support f2c: 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.

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 get in touch to ask questions. We have had a fair amount of practice at porting R to new platforms ....

Function and variable index

Concept index

Footnotes

if you have the source-code package files installed
Using the SunPro aka Forte aka Sun ONE cc and f95 compilers
On HP-UX fort77 is the POSIX compliant FORTRAN compiler, and comes second in the search list.
as well as its equivalence to the Rcomplex structure defined in R_ext/Complex.h.
In particular, avoid g77's -pedantic, which gives confusing error messages.
e.g., to use an optimized BLAS on Sun/Sparc

R Installation and Administration