# R Installation and Administration

This is a guide to installation and administration for R.

This manual is for R, version 4.3.3 Patched (2024-02-29).

Copyright © 2001–2023 R Core Team

> Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies.

> Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one.

> Permission is granted to copy and distribute translations of this manual into another language, under the above conditions for modified versions, except that this permission notice may be stated in a translation approved by the R Core Team.

## Table of Contents

- 1 Obtaining R
  - 1.1 Getting and unpacking the sources
  - 1.2 Getting patched and development versions
    - 1.2.1 Using Subversion and rsync
- 2 Installing R under Unix-alikes
  - 2.1 Simple compilation
  - 2.2 Help options
  - 2.3 Making the manuals
  - 2.4 Installation
  - 2.5 Uninstallation
  - 2.6 Sub-architectures
    - 2.6.1 Multilib
  - 2.7 Other Options
    - 2.7.1 Debugging Symbols
    - 2.7.2 OpenMP Support
    - 2.7.3 C++ Support
    - 2.7.4 C standards
    - 2.7.5 Link-Time Optimization
      - 2.7.5.1 LTO with GCC
      - 2.7.5.2 LTO with LLVM
      - 2.7.5.3 LTO for package checking
  - 2.8 Testing an Installation
- 3 Installing R under Windows
  - 3.1 Building from source
    - 3.1.1 The Windows toolset
    - 3.1.2 LaTeX
  - 3.2 Checking the build
  - 3.3 Testing an Installation
- 4 Installing R under macOS
  - 4.1 Running R under macOS
  - 4.2 Uninstalling under macOS
  - 4.3 Multiple versions
- 5 Running R
- 6 Add-on packages
  - 6.1 Default packages
  - 6.2 Managing libraries
  - 6.3 Installing packages
    - 6.3.1 Windows
    - 6.3.2 macOS
    - 6.3.3 Customizing package compilation
    - 6.3.4 Multiple sub-architectures
    - 6.3.5 Byte-compilation
    - 6.3.6 External software
  - 6.4 Updating packages
  - 6.5 Removing packages
  - 6.6 Setting up a package repository
  - 6.7 Checking installed source packages
- 7 Internationalization and Localization
  - 7.1 Locales
    - 7.1.1 Locales under Unix-alikes
    - 7.1.2 Locales under Windows
    - 7.1.3 Locales under macOS
  - 7.2 Localization of messages
- 8 Choosing between 32- and 64-bit builds
- 9 The standalone Rmath library
  - 9.1 Unix-alikes
  - 9.2 Windows
- Appendix A Essential and useful other programs under a Unix-alike
  - A.1 Essential programs and libraries
  - A.2 Useful libraries and programs
    - A.2.1 Tcl/Tk
    - A.2.2 Java support
    - A.2.3 Other compiled languages
  - A.3 Linear algebra
    - A.3.1 BLAS
      - A.3.1.1 ATLAS
      - A.3.1.2 OpenBLAS and BLIS
      - A.3.1.3 Intel MKL
      - A.3.1.4 Shared BLAS
    - A.3.2 LAPACK
    - A.3.3 Caveats
- Appendix B Configuration on a Unix-alike
  - B.1 Configuration options
  - B.2 Internationalization support
  - B.3 Configuration variables
    - B.3.1 Setting paper size
    - B.3.2 Setting the browsers
    - B.3.3 Compilation flags
    - B.3.4 Making manuals
  - B.4 Setting the shell
  - B.5 Using make
  - B.6 Using Fortran
  - B.7 Compile and load flags
  - B.8 Maintainer mode
- Appendix C Platform notes
  - C.1 X11 issues
  - C.2 Linux
    - C.2.1 Clang
    - C.2.2 flang
    - C.2.3 Intel compilers
      - C.2.3.1 ‘Classic’ Intel compilers
  - C.3 macOS
    - C.3.1 Prerequisites
    - C.3.2 Fortran compiler
    - C.3.3 Cairo graphics
    - C.3.4 Other C/C++ compilers
    - C.3.5 Other libraries
    - C.3.6 Tcl/Tk headers and libraries
    - C.3.7 Java
    - C.3.8 Frameworks
    - C.3.9 Building R.app
    - C.3.10 Building binary packages
    - C.3.11 Building for Intel on ‘`arm64`’
    - C.3.12 Installer
  - C.4 FreeBSD
  - C.5 OpenBSD
  - C.6 Cygwin
  - C.7 New platforms
- Function and variable index
- Concept index
- Environment variable index

## 1 Obtaining R

Sources, binaries and documentation for R can be obtained via CRAN, the “Comprehensive R Archive Network” whose current members are listed at https://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

    tar -xf R-x.y.z.tar.gz

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

    gzip -dc R-x.y.z.tar.gz | tar -xf -

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 fairly 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

    tar --no-same-owner -xf R-x.y.z.tar.gz

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 (4.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 https://stat.ethz.ch/R/daily/. 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 https://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

    svn checkout https://svn.r-project.org/R/trunk/ path

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 (and will give a error early in the `make` process): 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 directory 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 ‘`https://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`)

    wget -r -l1 --no-parent -A\*.gz -nd -P src/library/Recommended \
      https://CRAN.R-project.org/src/contrib/dir
    ./tools/link-recommended

## 2 Installing R under Unix-alikes

R will configure and build under most common Unix and Unix-alike platforms including ‘`cpu-*-linux-gnu`’ for the ‘`alpha`’, ‘`arm64`’ (also known as ‘`aarch64`’, ‘`ix86`’, ‘`mips`’, ‘`mipsel`’#, ‘`ppc64`’, ‘`riscv64`’, ‘`s390x`’, ‘`sparc64`’, and ‘`x86_64`’ CPUs, ‘`x86_64-apple-darwin`’ and ‘`aarch64-apple-darwin`’3 as well as perhaps (it is tested less frequently on these platforms) ‘`x86_64-*-freebsd`’, ‘`x86_64-*-openbsd`’ and ‘`powerpc-ibm-aix6*`’

In addition, binary distributions are available for some common Linux distributions (see the FAQ for current details) and for macOS. These are installed in platform-specific ways, so for the rest of this chapter we consider only building from the sources.

Cross-building is not possible: installing R builds a minimal version of R and then runs many R scripts to complete the build.

### 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 either the environment variable `TMPDIR` is either unset (and `/tmp` exists and can be written in and scripts can be executed from) or points to the absolute path to a valid temporary directory (one from which execution of scripts is allowed) which does not contain spaces.4

Choose a directory 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 (At this point North American readers should consult Setting paper size.) Issue the following commands:

    ./configure
    make

(See Using make if your make is not called ‘`make`’.) Users of Debian-based 64-bit systems5 may need

    ./configure LIBnn=lib
    make

Then check the built system works correctly by

    make check

Failures are not necessarily problems as they might be caused by missing functionality, 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).

More comprehensive testing can be done by

    make check-devel

or

    make check-all

see Testing an Installation for the possibilities of doing this in parallel. Note that these checks are only run completely if the recommended packages are installed. If you have a local CRAN mirror, these checks can be speeded up by either setting environment variable `R_CRAN_WEB` to its URL, or having a file `.R/repositories` specifying it (see `?setRepositories`).

Parallel make is supported for building R but not for the ‘`check`’ targets (as the output is likely to be unreadably interleaved, although where supported6 GNU make’s `-O` may help).

If the `configure` and `make` commands execute successfully, a shell-script front-end called `R` will be created and copied to `R_HOME/bin`. You can link or 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

    cd BUILDDIR
    TOP_SRCDIR/configure
    make

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. It is unlikely to work if the source directory has previously been used for a build.)

There are many settings which can be customized when building R and most are described in the file `config.site` in the top-level source directory. This can be edited, but for an installation using `BUILDDIR` it is better to put the changed settings in a newly-created file `config.site` in 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 https://CRAN.R-project.org/doc/FAQ/R-FAQ.html which always has the version for the latest release of R).

Note: if you already have R installed, check that where you installed R replaces or comes earlier in your path than the previous installation. Some systems are set up to have `/usr/bin` (the standard place for a system installation) ahead of `/usr/local/bin` (the default place for installation of R) in their default path, and some do not have `/usr/local/bin` on the default path.

### 2.2 Help options

R by default provides help pages as plain text displayed in a pager, with the options (see the help for `help`) of displaying help as HTML or PDF.

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

There is a set of manuals that can be built from the sources,

‘`fullrefman`’

  Printed versions of all the help pages for base and recommended packages (around 3750 pages).

‘`refman`’

  Printed versions of the help pages for selected base packages (around 2200 pages)

‘`R-FAQ`’

  R FAQ

‘`R-intro`’

  “An Introduction to R”.

‘`R-data`’

  “R Data Import/Export”.

‘`R-admin`’

  “R Installation and Administration”, this manual.

‘`R-exts`’

  “Writing R Extensions”.

‘`R-lang`’

  “The R Language Definition”.

To make these (with ‘`fullrefman`’ rather than ‘`refman`’), use

    make pdf      to create PDF versions
    make info     to create info files (not ‘refman’ nor ‘fullrefman’).

You will not be able to build any of these unless you have `texi2any` version 5.1 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 path to `texi2any` can be set by macro ‘`TEXI2ANY`’ in `config.site`. NB: `texi2any` requires `perl`.

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`. The usual value for North America would be ‘`letter`’.)

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

`times`

  (The default.) Using standard PostScript fonts, Times Roman, Helvetica and Courier. This works well both for on-screen viewing and for printing. One disadvantage is that the Usage and Examples sections may come out rather wide: this can be overcome by using in addition either of the options `inconsolata` (on a Unix-alike only if found by `configure`) or `beramono`, which replace the Courier monospaced font by Inconsolata or Bera Sans mono respectively. (You will need the LaTeX package inconsolata 7 or bera installed.)

  Note that in most LaTeX installations this will not actually use the standard fonts for PDF, but rather embed the URW clones NimbusRom, NimbusSans and (for Courier, if used) NimbusMon.

  This needs LaTeX packages times, helvetic and (if used) courier installed.

`lm`

  Using the Latin Modern fonts. These are not often installed as part of a TeX distribution, but can obtained from https://www.ctan.org/tex-archive/fonts/ps-type1/lm/ and mirrors. This uses fonts rather similar to Computer Modern, but is not so good on-screen as `times`.

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, using `make -e`.) The usual8 default value for `R_RD4PDF` is ‘`times,inconsolata,hyper`’: omit ‘`inconsolata`’ if you do not have LaTeX package inconsolata installed. As from R 4.2.0, ‘`hyper`’ is always enabled (with a fallback if LaTeX package hyperref is not installed).

Further options, e.g for hyperref, can be included in a file `Rd.cfg` somewhere on your LaTeX search path. For example, if you prefer to hyperlink the text and not the page number in the table of contents use

    \ifthenelse{\boolean{Rd@use@hyper}}{\hypersetup{linktoc=section}}{}

or

    \ifthenelse{\boolean{Rd@use@hyper}}{\hypersetup{linktoc=all}}{}

to hyperlink both text and page number.

Any generated PDF manuals can be compacted by

    make compact-pdf

provided `qpdf` and `gs` are available (see `?tools::compactPDF` for how to specify them if not on the path).

Ebook versions of most of the manuals in one or both of `.epub` and `.mobi` formats can be made by running in `doc/manual` one of

    make ebooks
    make epub
    make mobi

This requires `ebook-convert` from `Calibre`, or from most Linux distributions. If necessary the path to `ebook-convert` can be set as make macro `EBOOK` by editing `doc/manual/Makefile` (which contains a commented value suitable for macOS) or using `make -e`.

### 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.

After

    ./configure
    make
    make check

(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

    make install

A parallel make can be used (but run `make` before `make install`). Those using GNU `make` 4.0 or later may want to use `make -j n -O` to avoid interleaving of output.

This will install to the following directories:

`prefix/bin` or `bindir`

  the front-end shell script and other scripts and executables

`prefix/man/man1` or `mandir/man1`

  the man page

`prefix/LIBnn/R` or `libdir/R`

  all the rest (libraries, on-line help system, …). Here LIBnn is usually ‘`lib`’, but may be ‘`lib64`’ on some 64-bit Linux systems. This is known as the R home directory.

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

    ./configure --prefix=/where/you/want/R/to/go

where the value should be an absolute path. 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`. The installation may need to be done by the owner of `prefix`, often a root account.

There is the option of using `make install-strip` (see Debugging Symbols).

You can install into another directory tree by using

    make prefix=/path/to/here install

at least with GNU `make` (but not some other 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-4.3.3`.

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

    make install rhome=/usr/local/lib64/R-4.3.3

will use a version-specific R home on a non-Debian Linux 64-bit system.

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

    make prefix=/path/to/here install-libR

where `prefix` is optional, and `libdir` will give more precise control.9 However, you should not install to a directory mentioned in `LDPATHS` (e.g. `/usr/local/lib64`) if you intend to work with multiple versions of R, since that directory may be given precedence over the `lib` directory of other R installations.

    make install-strip

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 some aspects (such as installing source packages) will not work.

To install info and PDF versions of the manuals, use one or both of

    make install-info
    make install-pdf

Once again, it is optional to specify `prefix`, `libdir` or `rhome` (the PDF manuals are installed under the R home directory).

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 https://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

    make install-tests

which populates a `tests` directory in the installation.

### 2.5 Uninstallation

You can uninstall R by

    make uninstall

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.

An installed shared/static `libR` can be uninstalled by

    make prefix=/path/to/here uninstall-libR

### 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 Linux for different CPUs or 32- and 64-bit builds.

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 software 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 74Mb, and adding a 32-bit build added 6Mb. If you have installed multiple builds you can select which build to run by

    R --arch=name

and just running ‘`R`’ will run the last build that was installed.

`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

    R --arch=name CMD INSTALL --libs-only pkg1 pkg2 …

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.

When running post-install tests with sub-architectures, use

    R --arch=name CMD make check[-devel|all]

to select a sub-architecture to check.

Sub-architectures were also used on Windows, but by selecting executables within the appropriate `bin` directory, `R_HOME/bin/x64`. For backwards compatibility there are executables `R_HOME/bin/R.exe` and `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 option10 and finally from the installation default (which is 32-bit for a combined 32/64 bit R installation). R 4.2.0 follows the scheme, but supports and includes only 64-bit builds.

#### 2.6.1 Multilib

For some Linux distributions11, there is an alternative mechanism for mixing 32-bit and 64-bit libraries known as multilib. If the 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 selected using the `setarch` command. For example, a 32-bit build may be run by

    setarch i686 R

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).

There is a potential problem with packages using Java, as the post-install for a ‘`i686`’ 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)

    export JAVA_HOME=<path to jre directory of 32-bit Java>
    setarch i686 R CMD javareconf

to get a suitable setting.

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

There are many other installation options, most of which are listed by `configure --help`. Almost all of those not listed elsewhere in this manual are either standard `autoconf` options not relevant to R or intended for specialist uses by the R developers.

One that may be useful when working on R itself is the option `--disable-byte-compiled-packages`, which ensures that the base and recommended packages are not byte-compiled. (Alternatively the (make or environment) variable `R_NO_BASE_COMPILE` can be set to a non-empty value for the duration of the build.)

Option `--with-internal-tzcode` makes use of R’s own code and copy of the IANA database for managing timezones. This will be preferred where there are issues with the system implementation, usually involving times after 2037 or before 1916. An alternative time-zone directory12 can be used, pointed to by environment variable `TZDIR`: this should contain files such as `Europe/London`. On all tested OSes the system timezone was deduced correctly, but if necessary it can be set as the value of environment variable `TZ`.

Options `--with-internal-iswxxxxx`, `--with-internal-towlower` and `--with-internal-wcwidth` were introduced in R 4.1.0. These control the replacement of the system wide-character classification (such as `iswprint`), case-changing (`wctrans`) and width (`wcwidth` and `wcswidth`) functions by ones contained in the R sources. Replacement of the classification functions has been done for many years on macOS and AIX (and Windows): option `--with-internal-iswxxxxx` allows this to be suppressed on those platforms or used on others. Replacing the case-changing functions was new in R 4.1.0 and the default on macOS (and on Windows since R 4.2.0). Replacement of the width functions has also been done for many years and remains the default. These options will only matter to those working with non-ASCII character data, especially in languages written in a non-Western script13 (which includes ‘symbols’ such as emoji). Note that one of those `iswxxxxx` is `iswprint` which is used to decide whether to output a character as a glyph or as a ‘`\U{xxxxxx}`’ escape—for example, try ‘`"\U1f600"`’, an emoji. The width functions are of most importance in East Asian locale: their values differ between such locales. (Replacing the system functions provides a degree of platform-independence (including to OS updates) but replaces it with a dependence on the R version.)

#### 2.7.1 Debugging Symbols

By default, `configure` adds a flag (usually `-g`) to the compilation flags for C, Fortran and CXX sources. This will slow down compilation and increase object sizes of both R and packages, so it may be a good idea to change those flags (set ‘`CFLAGS`’ etc in `config.site` before configuring, or edit files `Makeconf` and `etc/Makeconf` between running `configure` and `make`).

Having debugging symbols available is useful both when running R under a debugger (e.g., `R -d gdb`) and when using sanitizers and `valgrind`, all things intended for experts.

Debugging symbols (and some others) can be ‘stripped’ on installation by using

    make install-strip

How well this is supported depends on the platform: it works best on those using GNU `binutils`. On ‘`x86_64`’ Linux a typical reduction in overall size was from 92MB to 66MB. On macOS debugging symbols are not by default included in `.dylib` and `.so` files, so there is negligible difference.

#### 2.7.2 OpenMP Support

By default `configure` searches for suitable flags14 for OpenMP support for the C, C++ (default standard) and Fortran compilers.

Only the C result is currently used for R itself, and only if `MAIN_LD`/`DYLIB_LD` were not specified. This can be overridden by specifying

    R_OPENMP_CFLAGS

Use for packages has similar restrictions (involving `SHLIB_LD` and similar: note that as Fortran code is by default linked by the C (or C++) compiler, both need to support OpenMP) and can be overridden by specifying some of

    SHLIB_OPENMP_CFLAGS
    SHLIB_OPENMP_CXXFLAGS
    SHLIB_OPENMP_FFLAGS

Setting these to an empty value will disable OpenMP for that compiler (and configuring with `--disable-openmp` will disable all detection15 of OpenMP). The `configure` detection test is to compile and link a standalone OpenMP program, which is not the same as compiling a shared object and loading it into the C program of R’s executable. Note that overridden values are not tested.

#### 2.7.3 C++ Support

C++ is not used by R itself, but support is provided for installing packages with C++ code via `make` macros defined in file `etc/Makeconf` (and with explanations in file `config.site`):

    CXX
    CXXFLAGS
    CXXPICFLAGS
    CXXSTD

    CXX11
    CXX11STD
    CXX11FLAGS
    CXX11PICFLAGS

    CXX14
    CXX14STD
    CXX14FLAGS
    CXX14PICFLAGS

    CXX17
    CXX17STD
    CXX17FLAGS
    CXX17PICFLAGS

    CXX20
    CXX20STD
    CXX20FLAGS
    CXX20PICFLAGS

    CXX23
    CXX23STD
    CXX23FLAGS
    CXX23PICFLAGS

The macros `CXX` etc are those used by default for C++ code. `configure` will attempt to set the rest suitably, choosing for `CXXSTD` and `CXX11STD` a suitable flag such as `-std=c++11` for C++11 support (which is required if C++ is to be supported at all). inferred values can be overridden in file `config.site` or on the `configure` command line: user-supplied values will be tested by compiling some C++11/14/17/20/23 code.

It may be that there is no suitable flag for C++14/17/20/23 support with the default compiler, in which case a different compiler could be selected for `CXX14`/`CXX17`/`CXX20`/`CXX23` with its corresponding flags.

The `-std` flag is supported by the GCC, `clang++` and Intel compilers. Currently accepted values are (plus some synonyms)

    g++:     c++11 gnu+11 c++14 gnu++14 c++17 gnu++17 c++2a gnu++2a (from 8)
             c++20 gnu++20 (from 10) c++23 gnu++23 c++2b gnu++2b (from 11)
    Intel:   c++11  gnu+11 c++14 gnu++14 c++17 gnu++17
             c++20 gnu++20 (from 2021.1) c++2b gnu++2b (from 2022.2)

(Those for LLVM `clang++` are documented at https://clang.llvm.org/cxx_status.html, and follow `g++`: `-std=c++20` is supported from Clang 10, `-std=c++2b` from Clang 13 and `-std=c++23` from Clang 17. Apple Clang supports `-std=c++2b` from 13.1.6: version 15.0.0 does not support `-std=c++23`.)

‘Standards’ for `g++` starting with ‘`gnu`’ enable ‘GNU extensions’: what those are is hard to track down.

For the use of C++11 and later in R packages see the ‘Writing R Extensions’ manual. Prior to R 3.6.0 the default C++ standard was that of the compiler used: currently it is C++17 (if available): this can be overridden by setting ‘`CXXSTD`’ when R is configured.

https://en.cppreference.com/w/cpp/compiler_support indicates which versions of common compilers support (parts of) which C++ standards. GCC 5 was the minimum version with sufficient C++14 support. GCC introduced C++17 support gradually, but version 7 should suffice.

#### 2.7.4 C standards

Compiling R requires C99 or later: C11 and C17 are minor updates, but the substantial update planned for ‘C23’ (now expected ca April 2024) will also be supported.

As from R 4.3.0 there is support for packages to indicate their preferred C version. Macros `CC17`, `C17FLAGS`, `CC23` and `C23FLAGS` can be set in `config.site` (there are examples there). Those for C17 should support C17 or earlier and not allow C23 additions so for example `bool`, `true` and `false` can be used as identifiers. Those for C23 should support new types such as `bool`.

Some compilers warn enthusiastically about prototypes. For most, omitting `-Wstrict-prototypes` in `C17FLAGS` suffices. However, versions 15 and later of LLVM `clang` and 14.0.3 and later of Apple clang warn by default in all modes if `-Wall` or `-pedantic` is used, and may need `-Wno-strict-prototypes`.

#### 2.7.5 Link-Time Optimization

There is support for using link-time optimization (LTO) if the toolchain supports it: configure with flag `--enable-lto`. When LTO is enabled it is used for compiled code in add-on packages unless the flag `--enable-lto=R` is used16.

The main benefit seen to date from LTO has been detecting long-standing bugs in the ways packages pass arguments to compiled code and between compilation units. Benchmarking in 2020 with `gcc`/`gfortran` 10 showed gains of a few percent in increased performance and reduction in installed size for builds without debug symbols, but large size reductions for some packages17 with debug symbols. (Performance and size gains are said to be most often seen in complex C++ builds.)

Whether toolchains support LTO is often unclear: all of the C compiler, the Fortran compiler18 and linker have to support it, and support it by the same mechanism (so mixing compiler families may not work and a non-default linker may be needed). It has been supported by the GCC and LLVM projects for some years with diverging implementations.

LTO support was added in 2011 for GCC 4.5 on Linux but was little used before 2019: compiler support has steadily improved over those years and `--enable-lto=R` is nowadays used for some routine CRAN checking.

Unfortunately `--enable-lto` may be accepted but silently do nothing useful if some of the toolchain does not support LTO: this is less common than it once was.

Various macros can be set in file `config.site` to customize how LTO is used. If the Fortran compiler is not of the same family as the C/C++ compilers, set macro ‘`LTO_FC`’ (probably to empty). Macro ‘`LTO_LD`’ can be used to select an alternative linker should that be needed.

#### 2.7.5.1 LTO with GCC

This has been tested on Linux with `gcc`/`gfortran` 8 and later: that needed setting (e.g. in `config.site`)

    AR=gcc-ar
    RANLIB=gcc-ranlib

For non-system compilers or if those wrappers have not been installed one may need something like

    AR="ar --plugin=/path/to/liblto_plugin.so"
    RANLIB="ranlib --plugin=/path/to/liblto_plugin.so"

amd `NM` may be needed to be set analogously. (If using an LTO-enabled build to check packages, set environment variable `UserNM` 19 to ‘`gcc-nm`’.)

With GCC 5 and later it is possible to parallelize parts of the LTO linking process: set the make macro ‘`LTO`’ to something like ‘`LTO=-flto=8`’ (to use 8 threads), for example in file `config.site`.

Under some circumstances and for a few packages, the PIC flags have needed overriding on Linux with GCC 9 and later: e.g use in `config.site`:

    CPICFLAGS=-fPIC
    CXXPICFLAGS=-fPIC
    CXX11PICFLAGS=-fPIC
    CXX14PICFLAGS=-fPIC
    CXX17PICFLAGS=-fPIC
    CXX20PICFLAGS=-fPIC
    FPICFLAGS=-fPIC

We suggest only using these if the problem is encountered (it was not seen on CRAN with GCC 10 at the time of writing).

Note that R may need to be re-compiled after even a minor update to the compiler (e.g. from 10.1 to 10.2) but this may not be clear from confused compiler messages.

#### 2.7.5.2 LTO with LLVM

LLVM supports another type of LTO called ‘Thin LTO’ as well as a similar implementation to GCC, sometimes called ‘Full LTO’. (See https://clang.llvm.org/docs/ThinLTO.html.) Currently the LLVM compilers relevant to R are `clang` and `flang` for which this can be selected by setting macro ‘`LTO=-flto=thin`’. LLVM has

    AR=llvm-ar
    RANLIB=llvm-ranlib

(but macOS does not, and these are not needed there). Where the linker supports a parallel backend for Thin LTO this can be specified via the macro ‘`LTO_LD`’: see the URL above for per-linker settings and further linking optimizations.)

For example, on macOS one might use

    LTO=-flto=thin
    LTO_FC=
    LTO_LD=-Wl,-mllvm,-threads=4

to use Thin LTO with 4 threads for C/C++ code, but skip LTO for Fortran code compiled with `gfortran`.

It is said to be particularly beneficial to use `-O3` for `clang` in conjunction with LTO.

It seems that `flang` may support LTO, but with no documentation as yet.

The 2020s versions of Intel’s C/C++ compilers are based on LLVM and as such support LLVM-style LTO, both ‘full’ and ‘thin’. This might use something like

    LTO=-flto=thin -flto-jobs=8

#### 2.7.5.3 LTO for package checking

LTO effectively compiles all the source code in a package as a single compilation unit and so allows the compiler (with sufficient diagnostic flags such as `-Wall`) to check consistency between what are normally separate compilation units.

With `gcc`/`gfortran` 9.x and later20 LTO will flag inconsistencies in calls to Fortran subroutines/functions, both between Fortran source files and between Fortran and C/C++. `gfortran` 8.4, 9.2 and later can help understanding these by extracting C prototypes from Fortran source files with option `-fc-prototypes-external`, e.g. that (at the time of writing) Fortran `LOGICAL` corresponds to `int_least32_t *` in C.

### 2.8 Testing an Installation

Full post-installation testing is possible only if the test files have been installed with

    make install-tests

which populates a `tests` directory in the 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 RHOME` or from R as `R.home()`) and run

    cd tests
    ## followed by one of
    ../bin/R CMD make check
    ../bin/R CMD make check-devel
    ../bin/R CMD make check-all

and other useful targets are `test-BasePackages` and `test-Recommended` to 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 the 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).

Parallel checking of packages may be possible: set the environment variable `TEST_MC_CORES` to the maximum number of processes to be run in parallel. This affects both checking the package examples (part of `make check`) and package sources (part of `make check-devel` and `make check-recommended`). It does require a `make` command which supports the `make -j n` option: most do.

Alternatively, the installed R can be run, preferably with `--vanilla`. Then

    pdf("tests.pdf") ## optional, but prevents flashing graphics windows
    Sys.setenv(LC_COLLATE = "C", LC_TIME = "C", LANGUAGE = "en")
    tools::testInstalledBasic("both")
    tools::testInstalledPackages(scope = "base")
    tools::testInstalledPackages(scope = "recommended")

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 fewer tests than the first approach: in particular they do not test things which need Internet access—that can be tested by

    tools::testInstalledBasic("internet")

It is possible to test the installed packages (but not their package-specific tests) by `testInstalledPackages` even if `make install-tests` was not run. The outputs are written under the current directory unless a different one is specified by `outDir`.

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 (before starting the R session)

    LANGUAGE=en

and use a UTF-8 or Latin-1 locale.

## 3 Installing R under Windows

[The rest of this paragraph is only relevant after release.] 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 64-bit Windows.

R is best tested on current versions of Windows 10 and Windows Server 2022 with UTF-8 as the charset encoding. It works also on Windows 11. It runs on older versions of Windows, but normally with other charset encoding and may require manual installation of the Universal C Runtime (UCRT).

Your file system must allow long file names (as is likely except perhaps for some network-mounted systems). If it does not also support conversion to short name equivalents (a.k.a. DOS 8.3 names), then R must be installed in a path that does not contain spaces.

Installation is via the installer `R-4.3.3patched-win.exe`. Just double-click on the icon and follow the instructions. You can uninstall R from the Control Panel.

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

See the R Windows FAQ for more details on the binary installer and for information on use on older Windows systems.

### 3.1 Building from source

It is possible to use other 64-bit toolchains (including ‘MSYS2’) with UCRT support to build R, but this manual only documents that used for binary distributions of R 4.2.x and later. When using other toolchains, makefiles of R and packages may need to be adapted.

#### 3.1.1 The Windows toolset

The binary distribution of R is currently built with tools from Rtools43 for Windows. See Building R and packages for more details on how to use it.

The toolset includes compilers (GCC version 12.2.0 with selected additional patches) and runtime libraries from the ‘MinGW-w64’ project and a number of pre-compiled static libraries and headers used by R and R packages, compiled by ’MXE’ (M cross environment, with updates maintained by Tomas Kalibera). The toolset also includes build tools from the the ’MSYS2’ project. Additional build tools packaged by ’MSYS2’ may be installed via a package manager (‘`pacman`’).

The toolsets used for 64-bit Windows from 2008 to 2022 were based on MinGW-w64. 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 and from Martin Storsjo.

#### 3.1.2 LaTeX

Both building R and checking packages need a distribution of LaTeX installed, with the directory containing `pdflatex` on the path.

The ‘`MiKTeX`’ (https://miktex.org/) distribution of LaTeX is that used on CRAN. This can be set up to install extra packages ‘on the fly’ (without asking), which is the simplest way to use it. The ‘basic’ version of ‘`MiKTeX`’ will need to add some packages.21 In any case ensure that the inconsolata package is installed—you can check with the ‘`MiKTeX`’ Package Manager.

It is also possible to use the TeX Live distribution from https://www.tug.org/texlive/. (The CRAN package tinytex can install and manage a subset of TeX Live.)

### 3.2 Checking the build

You can test a build by running

    make check

The recommended packages can be checked by

    make check-recommended

Other levels of checking are

    make check-devel

for a more thorough check of the R functionality, and

    make check-all

for both `check-devel` and `check-recommended`.

If a test fails, there will almost always be a `.Rout.fail` file in the directory being checked (often `tests/Examples` or `tests`): examine the file to help pinpoint the problem.

Parallel checking of package sources (part of `make check-devel` and `make check-recommended`) is possible: see the environment variable `TEST_MC_CORES` to the maximum number of processes to be run in parallel.

### 3.3 Testing an Installation

The Windows installer contains a set of test files used when building R.

The toolset is not needed to run these tests, but more comprehensive analysis of errors will be given if `diff` is in the path.

Launch either `Rgui` or `Rterm` (preferred), preferably with `--vanilla`. Then run

    Sys.setenv(LC_COLLATE = "C", LC_TIME="C", LANGUAGE = "en")
    tools::testInstalledBasic("both")
    tools::testInstalledPackages(scope = "base")
    tools::testInstalledPackages(scope = "recommended")

runs the basic tests and then all the tests on the standard and recommended packages. These tests can be run from anywhere: `testInstalledBasic` writes results in the `tests` folder of the R home directory (as given by `R.home()`) and `testInstalledPackages` under the current directory unless a different one is specified by `outDir`.

For the `tests` folder to be writeable, one normally needs to install R to a directory other than the default `C:\Program Files`. The installer also allows to install R without Administrator privileges, see the R Windows FAQ for more details.

The results of `example(md5sums)` when testing tools may differ from the reference output as some files are installed with Windows’ CRLF line endings. Also, expect differences in `reg-plot-latin1.pdf`.

One can also run tests from the toolset shell (e.g. `bash`) similarly to a Unix-like installation. Move to the home directory of the R installation (as given by `R RHOME` or from R as `R.home()`) and run

    cd tests
    ## followed by one of
    ../bin/R CMD make check
    ../bin/R CMD make check-devel
    ../bin/R CMD make check-all

Remember that LaTeX needs to be on the path.

## 4 Installing R under macOS

[The rest of this paragraph is only relevant after release.] The front page of a CRAN site has a link ‘Download R for (Mac) OS X’ which takes you to a new page. Two files are offered for download, `R-4.3.3-arm64.pkg` and `R-4.3.3.pkg`. Both are for macOS 11 or later (Big Sur, Monterey, Ventura, …).

The first runs is for ‘Apple Silicon’ (aka ‘M1’, ‘M2’ or ’M3’) Macs, the second for older Macs with an ‘`x86_64`’ (Intel) CPU.

Package `R-4.3.3.pkg` also be installed on ‘Apple Silicon’ CPUs using ‘Rosetta’ emulation22, but the native build is preferred. It is a little faster (and for some tasks, considerably so) but may give different numerical results from the more common ‘`x86_64`’ platforms (on Windows, Linux, … as well as macOS) as ARM hardware lacks extended-precision floating-point operations.

It is important that if you use a binary installer package that your OS is fully updated: look at ‘Software Update’ in ’System Preferences’ to be sure.

To install, just double-click on the icon of the file you downloaded. At the ‘Installation Type’ stage, note the option to ‘Customize’. This currently shows four components: everyone will need the ‘R Framework’ component: the remaining components are optional. (The ‘Tcl/Tk’ component is needed to use package tcltk. The ‘Texinfo’ component is only needed by those installing source packages or R from its sources.)

Note for Ventura users: installation from the `Downloads` folder may not be allowed or may require additional authorization, so we suggest you download somewhere else such as your desktop or home folder.

These are Apple Installer packages. If you encounter any problem during the installation, please check the Installer log by clicking on the “Window” menu and item “Installer Log”. The full output (select “Show All Log”) is useful for tracking down problems. Note that the installer is clever enough to try to upgrade the last-installed version of the application where you installed it (which may not be where you want this time …).

Various parts of the build require XQuartz to be installed: see https://www.xquartz.org/releases/.23 These include the tcltk package and the `X11` graphics device: attempting to use these without XQuartz will remind you. This is also needed for some builds of the cairographics-based devices (which are not often used on macOS) such as `png(type = "cairo")` and `svg()` and some third-party packages (e.g. rgl).

If you update your macOS version, you should re-install R (and perhaps XQuartz): the installer may tailor the installation to the current version of the OS.

Installers for R-patched and R-devel are usually available from https://mac.R-project.org. (Some of these packages may be unsigned/not notarized: to install those Control/right/two-finger click, select ‘`Open With`’ and ‘`Installer`’.)

For building R from source, see macOS.

### 4.1 Running R under macOS

There are two ways to run R on macOS from a CRAN binary distribution.

There is a GUI console normally installed with the R icon in `/Applications` which you can run by double-clicking (e.g. from Launchpad or Finder). (If you cannot find it there it was possibly installed elsewhere so try searching for it in Spotlight.) This is usually referred to as R.APP to distinguish it from command-line R: its user manual is currently part of the macOS FAQ at https://cran.r-project.org/bin/macosx/RMacOSX-FAQ.html and can be viewed from R.APP’s ‘Help’ menu.

You can run command-line R and `Rscript` from a Terminal24 so these can be typed as commands as on any other Unix-alike: see the next chapter of this manual. There are some small differences which may surprise users of R on other platforms, notably the default location of the personal library directory (under `~/Library/R`, e.g. `~/Library/R/x86_64/4.2/library`), and that warnings, messages and other output to `stderr` are highlighted in bold.

Those using the `zsh` shell (the default for new user accounts as from Catalina) might find the command `R` being masked by the `zsh` builtin `r` (which recalls commands). One can use a full path to R in an alias, or add `disable r` to `~/.zshrc`.

If you have installed both installer packages on an `arm64` Mac, the last installed will be used.

It has been reported that running R.APP may fail if no preferences are stored, so if it fails when launched for the very first time, try it again (the first attempt will store some preferences).

Users of R.APP need to be aware of the ‘App Nap’ feature (https://developer.apple.com/library/archive/releasenotes/MacOSX/WhatsNewInOSX/Articles/MacOSX10_9.html) which can cause R tasks to appear to run very slowly when not producing output in the console. Here are ways to avoid it:

- Ensure that the console is completely visible (or at least the activity indicator at the top right corner is visible).
- In a Terminal, run

      defaults write org.R-project.R NSAppSleepDisabled -bool YES

  (see https://developer.apple.com/library/archive/releasenotes/MacOSX/WhatsNewInOSX/Articles/MacOSX10_9.html).

Using the `X11` graphics device or the X11-based versions of `View()` and `edit()` for data frames and matrices (the latter are the default for command-line R but not R.APP) requires XQuartz to be installed.

Under some rather nebulous circumstances messages have been seen from `fontconfig` about missing/unreadable configuration files when using cairo-based devices, especially `X11(type = "cairo")`. With XQuartz installed there are two `fontconfig` areas from different versions and it can help to set

    setenv FONTCONFIG_PATH /opt/X11/lib/X11/fontconfig

Another symptom has been that italic/oblique fonts are replaced by upright ones.

### 4.2 Uninstalling under macOS

R for macOS consists of two parts: the GUI (R.APP) and the R framework. Un-installation is as simple as removing those folders (e.g. by dragging them onto the Bin aka Trash). The typical installation will install the GUI into the `/Applications/R.app` folder and the R framework into the `/Library/Frameworks/R.framework` folder. The links to `R` and `Rscript` in `/usr/local/bin` should also be removed.

If you want to get rid of R more completely using a Terminal, simply run:

    sudo rm -Rf /Library/Frameworks/R.framework /Applications/R.app \
       /usr/local/bin/R /usr/local/bin/Rscript

The installation consists of up to four Apple packages:25 for the Intel build, `org.R-project.x86_64.R.fw.pkg`, `org.R-project.x86_64.R.GUI.pkg`, `org.r-project.x86_64.tcltk` and `org.r-project.x86_64.texinfo`. You can use `sudo pkgutil --forget` if you want the Apple Installer to forget about the package without deleting its files (useful for the R framework when installing multiple R versions in parallel), or after you have deleted the files. NB: the package names are case-sensitive and the R domain is named inconsistently.

Uninstalling the Tcl/Tk and Texinfo components (which are installed under `/opt/R/x86_64` on a ‘`x86_64`’ build and `/opt/R/arm64` for an ‘`arm64`’ one) is not as simple. You can list the files they installed in a Terminal by e.g.

    pkgutil --files org.r-project.x86_64.tcltk
    pkgutil --files org.r-project.x86_64.texinfo

(For the ‘Apple Silicon’ build, replace `x86_64` by `arm64`.) These are paths relative to `/`, the root of the file system.

If you are not compiling R nor installing packages from source you could remove all of `/opt/R/x86_64` or `/opt/R/arm64`.

### 4.3 Multiple versions

The installer will remove any previous version26 of the R framework which it finds installed. This can be avoided by using `pkgutil --forget` (see the previous section). However, note that different versions are installed under `/Library/Frameworks/R.framework/Versions` as `4.4` (or `4.4-arm64`), `4.3` and so on, so it is not possible to have different ‘`4.x.y`’ versions installed for the same ‘`x`’ and CPU type.

R.APP will always run the ‘current’ version, that is the last installed version.

## 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 should have default limits at least as large as these, but apparently NetBSD may not. Use the shell command `ulimit` (`sh`/`bash`) or `limit` (`csh`/`tcsh`) to check.) For some compilers27 and packages a larger stack size has been needed: 20-25MB has sufficed to date.

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. The path should be an absolute path not containing spaces28 (and it is best to avoid non-alphanumeric characters such as `+` or quotes).

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 starting 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()`. To avoid any confusion you will often see a library directory referred to as a ‘library tree’.

### 6.1 Default packages

The set of packages loaded on startup is by default

    > getOption("defaultPackages")
    [1] "datasets"  "utils"     "grDevices" "graphics"  "stats"     "methods"

(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. But it can also be used to customize R, e.g. for class use. `Rscript` also checks the environment variable `R_SCRIPT_DEFAULT_PACKAGES`; if set, this takes precedence over `R_DEFAULT_PACKAGES`.

### 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 recommended29 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 setting30 ‘`.Library.site`’ in `R_HOME/etc/Rprofile.site`, or (not recommended) by setting the environment variable `R_LIBS_SITE`.

Users can have one or more libraries, normally specified by the environment variable `R_LIBS_USER`. This has a default value (to see it, use ‘`Sys.getenv("R_LIBS_USER")`’ within an R session), but that is only 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.

Ensure that the environment variable `TMPDIR` is either unset (and `/tmp` exists and can be written in and executed from) or is the absolute path to a valid temporary directory, not containing spaces.

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.31 On most systems ‘`install.packages()`’ will allow packages to be selected from a list box (typically with thousands of items).

To install packages from source on a Unix-alike use in a terminal

    R CMD INSTALL -l /path/to/library pkg1 pkg2 …

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]`).

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 choose your nearest CRAN mirror using `chooseCRANmirror()`. Then download and install packages pkg1 and pkg2 by

    > install.packages(c("pkg1", "pkg2"))

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 personal 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("Rcmdr", dependencies = TRUE)

`install.packages` can install a source package from a local `.tar.gz` file (or a URL to such a 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, R-forge, rforge.net, local archives, local files, …). Function `setRepositories()` can select amongst those repositories that the R installation is aware of.

Something which sometimes puzzles users is that `install.packages()` may report that a package which they believe should be available is not found. Some possible reasons:

- The package, such as grid or tcltk, is part of R itself and not otherwise available.
- The package is not in the available repositories, so check which have been selected by

      getOption("repos")

- The package is available, but not for the current version of R or for the type of OS (Unix/Windows). To retrieve the information on available versions of package `pkg`, use

      av <- available.packages(filters=list())
      av[av[, "Package"] == pkg, ]

  in your R session, and look at the ‘`Depends`’ and ‘`OS_type`’ fields (there may be more than one matching entry). If the package depends on a version of R later than the one in use, it is possible that an earlier version is available which will work with your version of R: for CRAN look for ‘Old sources’ on the package’s CRAN landing page and manually retrieve an appropriate version (of comparable age to your version of R).

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 macOS) 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) first at the list of binary versions of packages available for your version of R and downloads the latest versions (if any). If no binary version is available or the source version is newer, it will install the source versions of packages without compiled C/C++/Fortran code, and offer to do so for those with, if `make` is available (and this can be tuned by option `"install.packages.compile.from.source"`).

On Windows `install.packages` can also install a binary package from a local `zip` file (or the URL of such a 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 distributed as a single binary containing either or both architectures (32- and 64-bit). From R 4.2.0, they always contain only the 64-bit architecture.

`R CMD INSTALL` works in Windows to install source packages. No additional tools are needed if the package does not contain compiled code, and `install.packages(type="source")` will work for such packages. Those with compiled code need the tools (see The Windows toolset). The tools are found automatically by R when installed by the toolset installer. See Building R and packages for more details.

Occasional permission problems after unpacking source packages have been seen on some 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 https://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 (only 64-bit builds and installs are supported since R 4.2.0). 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 use32 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 that zip file on Windows. However, such a package can be installed from the sources on Windows without any additional tools.

#### 6.3.2 macOS

On macOS `install.packages` works as it does on other Unix-alike systems, but there is an additional type `mac.binary` (available for the CRAN distribution but not when compiling R from source) which can be passed to `install.packages` in order to download and install binary packages from a suitable repository. These binary package files for macOS have the extension ‘`.tgz`’. The R.APP GUI provides menus for installation of either binary or source packages, from CRAN, other repositories or local files.

On R builds using binary packages, the default is type `both`: this looks first at the list of binary packages available for your version of R and installs the latest versions (if any). If no binary version is available or the source version is newer, it will install the source versions of packages without compiled C/C++/Fortran code and offer to do so for those with, if `make` is available.

Note that most binary packages which include compiled code are tied to a particular series (e.g. R 4.2.x or 4.3.x) of R.

Installing source packages which do not contain compiled code should work with no additional tools. For others you will need the ‘Command Line Tools’ for `Xcode` and compilers which match those used to build R, plus a Fortran compiler for packages which contain Fortran code: see macOS.

Package rJava and those which depend on it need a Java runtime installed and several packages need X11 installed, including those using Tk. See macOS and Java. Package rjags needs a build of JAGS installed under `/usr/local`, such as those at https://sourceforge.net/projects/mcmc-jags/files/JAGS/4.x/Mac%20OS%20X/.

Tcl/Tk extension `BWidget` used to be distributed with R but no longer is; `Tktable` has been distributed with most versions of R (but not 4.0.0 and not ‘`arm64`’ builds of 4.1.0 or 4.1.1).

The default compilers specified are shown in file `/Library/Frameworks/R.framework/Resources/etc/Makeconf`. At the time of writing those settings assumed that the C, Fortran and C++ compilers were on the path (see macOS). The settings can be changed, either by editing that file or in a file such as `~/.R/Makevars` (see the next section). Entries which may need to be changed include ‘`CC`’, ‘`CXX`’, ‘`FC`’, ‘`FLIBS`’ and the corresponding flags, and perhaps ‘`CXXCPP`’, ‘`DYLIB_LD`’, ‘`MAIN_LD`’, ‘`SHLIB_CXXLD`’ and ‘`SHLIB_LD`’, as well as their ‘`CXX11`’, ‘`CXX14`’, ‘`CXX17`’ and ‘`CXX20`’ variants.

So for example you could select a specific LLVM `clang` for both C and C++ with extensive checking by having in `~/.R/Makevars`

    CC = /usr/local/clang/bin/clang -isysroot
      /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk
    CXX = /usr/local/clang/bin/clang++ -isysroot
      /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk
    CXX11 = $CXX
    CXX14 = $CXX
    CXX17 = $CXX
    CXX20 = $CXX
    CFLAGS = -g -O2 -Wall -pedantic -Wconversion -Wno-sign-conversion
    CXXFLAGS = -g -O2 -Wall -pedantic -Wconversion -Wno-sign-conversion
    CXX11FLAGS = $CXXFLAGS
    CXX14FLAGS = $CXXFLAGS
    CXX17FLAGS = $CXXFLAGS
    CXX20FLAGS = $CXXFLAGS

(long lines split for the manual only) and for the current macOS distribution of `gfortran` at https://mac.r-project.org/tools/

    FC = /opt/gfortran/bin/gfortran
    (arm64)
    FLIBS =  -L/opt/gfortran/lib/gcc/aarch64-apple-darwin20.0/12.2.0
      -L/opt/gfortran/lib -lgfortran -lemutls_w -lquadmath
    (Intel)
    FLIBS =  -L/opt/gfortran/lib/gcc/x86_64-apple-darwin20.0/12.2.0
      -L/opt/gfortran/lib -lgfortran -lquadmath

(line broken here for the manual only).

If that `clang` build supports OpenMP, you can add

    SHLIB_OPENMP_CFLAGS = -fopenmp
    SHLIB_OPENMP_CXXFLAGS = -fopenmp

to compile OpenMP-using packages. It will also be necessary to arrange for the `libomp.dylib` library to be found at both install time and run time, for example by copying/linking it somewhere that is searched such as `/usr/local/lib`.

Apple includes many Open Source libraries in macOS but increasingly without the corresponding headers (not even in Xcode nor the Command Line Tools): they are often rather old versions. If installing packages from source using them it is usually easiest to install a statically-linked up-to-date copy of the Open Source package from its sources or from https://mac.r-project.org/bin/. But sometimes it is desirable/necessary to use Apple’s dynamically linked library, in which case appropriate headers could be extracted from the sources33 available via https://opensource.apple.com – this has been used for `iodbc`.

Those using Command Line Tools / Xcode 12 or later (as released for macOS 11 ‘Big Sur’) probably want to arrange that the flag

    -Wno-implicit-function-declaration

is part of `CFLAGS`. Apple has changed the default to make implicit declarations a compilation error and authors of packages and external software have been unaware that this might be done — most issues seen were in `configure` scripts.

Some care may be needed with selecting compilers when installing external software for use with packages. The ‘system’ compilers as used when building R are `clang` and `clang++`, but the Apple toolchain also provides compilers called `gcc` and `g++` which despite their names are based on LLVM and `libc++` like the system ones and which behave in almost the same way as the system ones. Most Open Source software has a `configure` script developed using GNU `autoconf` and hence will select `gcc` and `g++` as the default compilers: this usually works fine. For consistency one can use

    ./configure CC=clang CFLAGS=-O2 CXX=clang++ CXXFLAGS=-O2

(avoiding `autoconf`’s default `-g`). Be careful if you put the `/usr/local/gfortran/bin` directory on your path as that may contain (real) `gcc` and `g++` which may be found rather the Apple-provided commands, and may not be able to find the headers and libraries34 of the SDK. As from R 4.3.0, `R CMD INSTALL` and `install.packages()` try to invoke `configure` with the same compilers and flags used to build R.

For ‘`arm64`’, not all configure scripts have been updated to recognize the platform and so might need the flag `--build=aarch64-apple-darwin20.1.0`. Also, be aware that running the compilers from a ‘`x86_64`’ application switches them to generating code for that CPU: this applies to a Terminal, a shell, older `cmake` or (non-system) `make`, and from `R CMD INSTALL` or `install.packages()`. One can use

    ./configure CC="clang -arch arm64" CFLAGS=-O2 CXX="clang++ -arch arm64" CXXFLAGS=-O2

to force ‘`arm64`’ code.

#### 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`. The full path to an alternative personal file35 can be specified via the environment variable `R_MAKEVARS_USER`.

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, or for `clang`.

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

    ## for C code
    CFLAGS = -g -O -mtune=native
    ## for C++ code
    CXXFLAGS = -g -O -mtune=native
    ## for C++11 code
    CXX11FLAGS = -g -O -mtune=native
    ## for fixed-form Fortran code
    FFLAGS = -g -O -mtune=native
    ## for C17 code
    C17FLAGS = -g -O -mtune=native -Wno-strict-prototypes

Note that if you have specified a non-default C++ or C standard, you need to set the flag(s) appropriate to that standard.

Another use is to override the settings in a binary installation of R. For example, for the current distribution of `gfortran` at https://mac.r-project.org/tools/

    FC = /opt/gfortran/bin/gfortran
    (arm64)
    FLIBS =  -L/opt/gfortran/lib/gcc/aarch64-apple-darwin20.0/12.2.0
      -L/opt/gfortran/lib -lgfortran -lemutls_w -lquadmath
    (Intel)
    FLIBS =  -L/opt/gfortran/lib/gcc/x86_64-apple-darwin20.0/12.2.0
      -L/opt/gfortran/lib -lgfortran -lquadmath

(line broken here for the manual only).

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`, and the path to an alternative file can be specified by environment variable `R_MAKEVARS_SITE`.

Note that these mechanisms do not work with packages which fail to pass settings down to sub-makes, perhaps reading `etc/Makeconf` in makefiles in subdirectories. Fortunately such packages are unusual.

#### 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 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. The exceptions are

Unix-alikes

  where there is an `configure` script, or a file `src/Makefile`.

Windows

  where there is a non-empty `configure.win` script, or a file `src/Makefile.win` (with some exceptions where the package is known to have an architecture-independent `configure.win`, or if `--force-biarch` or field ‘`Biarch`’ in the `DESCRIPTION` file is used to assert so).

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

    R CMD INSTALL --libs-only pkg

using the path to `R` or `R --arch` to select the additional sub-architecture. 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

As from R 3.6.0, all packages are by default byte-compiled.

Byte-compilation can be controlled on a per-package basis by the ‘`ByteCompile`’ field in the `DESCRIPTION` file.

#### 6.3.6 External software

Some R packages contain compiled code which links to external software libraries. Unless the external library is statically linked (which is done as much as possible for binary packages on Windows and macOS), the libraries have to be found when the package is loaded and not just when it is installed. How this should be done depends on the OS (and in some cases the version).

For Unix-alikes except macOS the primary mechanism is the `ld.so` cache controlled by `ldconfig`: external dynamic libraries recorded in that cache will be found. Standard library locations will be covered by the cache, and well-designed software will add its locations (as for example openmpi does on Fedora). The secondary mechanism is to consult the environment variable `LD_LIBRARY_PATH`. The R script controls that variable, and sets it to the concatenation of `R_LD_LIBRARY_PATH`, `R_JAVA_LD_LIBRARY_PATH` and the environment value of `LD_LIBRARY_PATH`. The first two have defaults which are normally set when R is installed (but can be overridden in the environment) so `LD_LIBRARY_PATH` is the best choice for a user to set.

On macOS the primary mechanism is to embed the absolute path to dependent dynamic libraries into an object when it is compiled. Few R packages arrange to do so, but it can be edited36 via `install_name_tool` — that only deals with direct dependencies and those would also need to be compiled to include the absolute paths of their dependencies. If the choice of absolute path is to be deferred to load time, how they are resolved is described in `man dyld`: the role of `LD_LIBRARY_PATH` is replaced on macOS by `DYLD_LIBRARY_PATH` and `DYLD_FALLBACK_LIBRARY_PATH`. Running `R CMD otool -L` on the package shared object will show where (if anywhere) its dependencies are resolved. `DYLD_FALLBACK_LIBRARY_PATH` is preferred (and it is that which is manipulated by the R script), but as from 10.11 (‘El Capitan’) the default behaviour had been changed for security reasons to discard these environment variables when invoking a shell script (and `R` is a shell script). That makes the only portable option to set `R_LD_LIBRARY_PATH` in the environment, something like

    export R_LD_LIBRARY_PATH="`R RHOME`/lib:/opt/local/lib"

The precise rules for where Windows looks for DLLs are complex and depend on the version of Windows. But for present purposes the main solution is to put the directories containing the DLLs the package links to (and any those DLLs link to) on the `PATH`.

The danger with any of the methods which involve setting environment variables is of inadvertently masking a system library. This is less for `DYLD_FALLBACK_LIBRARY_PATH` and for appending to `PATH` on Windows (as it should already contain the system library paths).

### 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. It 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

    > inst <- packageStatus()$inst
    > inst[inst$Status != "ok", c("Package", "Version", "Status")]
                      Package Version      Status
    Biobase           Biobase   2.8.0 unavailable
    RCurl               RCurl   1.4-2     upgrade
    Rgraphviz       Rgraphviz  1.26.0 unavailable
    rgdal               rgdal  0.6-27     upgrade

### 6.5 Removing packages

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

    R CMD REMOVE -l /path/to/library pkg1 pkg2 …

From a running R process they can be removed by

    > remove.packages(c("pkg1", "pkg2"),
                      lib = file.path("path", "to", "library"))

Finally, 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 https://www.stats.ox.ac.uk/pub/RWin/: this must be an URL scheme that `download.packages` supports (which also includes ‘`https://`’, ‘`ftp://`’ and ‘`file://`’). Under that base URL there should be directory trees for one or more of the following types of package distributions:

- `"source"`: located at `src/contrib` and containing `.tar.gz` files. Other forms of compression can be used, e.g. `.tar.bz2` or `.tar.xz` files. Complete repositories contain the sources corresponding to any binary packages, and in any case it is wise to have a `src/contrib` area with a possibly empty `PACKAGES` file.
- `"win.binary"`: located at `bin/windows/contrib/x.y` for R versions x.y.z and containing `.zip` files for Windows.
- `"mac.binary"`: located at `bin/macosx/contrib/4.y` for the CRAN builds for macOS for R versions 4.y.z, containing `.tgz` files.
- `"mac.binary.el-capitan"`: located at `bin/macosx/el-capitan/contrib/3.y` for the CRAN builds for R versions 3.y.z, containing `.tgz` files.

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 `PACKAGES.rds` and `PACKAGES.gz` files, downloaded in preference to `PACKAGES`. (If you have a mis-configured server that does not report correctly non-existent files you may need these files.)

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

Incomplete repositories are better specified via a `contriburl` argument than via being set as a repository.

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

    Path: path/to/subdirectory

—once again `write_PACKAGES` is the simplest way to set this up.

### 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 `pkg` (or a tarball filename):

    R CMD INSTALL -l libdir pkg > pkg.log 2>&1
    R CMD check -l libdir --install=check:pkg.log pkg

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

    R --arch arch CMD check -l libdir --extra-arch --install=check:pkg.log pkg

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 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

    .../bin/x64/Rcmd INSTALL -l libdir tarball --build > pkg.log 2>&1

## 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.

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

- A human language. These are generally specified by a lower-case two-character abbreviation following ISO 639 (see e.g. https://en.wikipedia.org/wiki/ISO_639-1).
- A ‘territory’, used mainly to specify the currency. These are generally specified by an upper-case two-character abbreviation following ISO 3166 (see e.g. https://en.wikipedia.org/wiki/ISO_3166).
- A charset encoding, which determines both how a byte stream should be divided into characters, and which characters the subsequences of bytes represent. Sometimes the combination of language and territory is used to specify the encoding, for example to distinguish between traditional and simplified Chinese.
- Optionally, a modifier, for example to indicate that Austria is to be considered pre- or post-Euro. The modifier is also used to indicate the script (`@latin`, `@cyrillic` for Serbian, `@iqtelif`) or language dialect (e.g. `@saaho`, a dialect of Afar, and `@bokmal` and `@nynorsk`, dialects of Norwegian regarded by some OSes as separate languages, `no` and `nn`).

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.

#### 7.1.1 Locales under Unix-alikes

Modern Linux uses the XPG 37 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`’.

Note that whereas UTF-8 locales are nowadays almost universally used, locales such as ‘`en_GB`’ use 8-bit encodings for backwards compatibility.

#### 7.1.2 Locales under Windows

Windows also uses locales, but specified in a rather less concise way. Most users will encounter locales only via drop-down menus, but more information and lists can be found by searching for ‘`Windows language country strings`’).

It offers only one encoding per language.

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 macOS

macOS supports locales in its own particular way, but the R GUI tries to make this easier for users. See https://developer.apple.com/library/archive/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 sometimes does when logging in remotely and for batch jobs: note whether `Terminal` sets the `LANG` environment variable is an (advanced) preference, but does so by default).

Internally macOS uses a form similar to Linux: 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 then38 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`, provided 39 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. Note that translated messages may be cached, so attempting to change the language of an error that has already been output in another language may not work.

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.

- Domain `R` for the C-level error and warning messages from the R interpreter.
- Domain `R-pkg` for the R `stop`, `warning` and `message` messages in each package, including `R-base` for the base package.
- Domain `pkg` for the C-level messages in each package.
- Domain `RGui` for the menus etc of the R for Windows GUI front-end.

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

R can be built without support for translations, but it is enabled by default.

R-level and C-level domains are subtly different, for example in the way strings are canonicalized before being passed for translation.

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.40 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 are 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 single 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’41 is used.

See https://developer.r-project.org/Translations30.html for how to prepare and install translation catalogues.

## 8 Choosing between 32- and 64-bit builds

Almost all current CPUs have both 32- and 64-bit sets of instructions. Some 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 64-bit version is the default and increasingly only that is supported—for example macOS has been 64-bit-only since Catalina (released in 2019) and R supports only 64-bit Windows since R 4.2.0.

All current versions of R use 32-bit integers (this is enforced in the build) and ISO/IEC 6055942 double-precision reals, and so compute to the same precision43 and with the same limits on the sizes of numerical quantities. The principal difference is in the size of the pointers.

64-bit builds have both advantages and disadvantages:

- The total virtual memory space made available to a 32-bit process is limited by the pointer size to 4GB, and on most OSes to 3GB (or even 2GB). The limits for 64-bit processes are much larger (e.g. 8–128TB).

  R allocates memory for large objects as needed, and removes any unused ones at garbage collection. When the sizes of objects become an appreciable fraction of the address limit, fragmentation of the address space becomes an issue and there may be no hole available that is the size requested. This can cause more frequent garbage collection or the inability to allocate large objects. As a guide, this will become an issue for 32-bit builds with objects more than 10% of the size of the address space (around 300Mb) or when the total size of objects in use is around one third (around 1Gb).

- Only 64-bit builds support ‘long vectors’, those with 2^{31} or more elements (which needs at least 16GB of storage for each numeric vector).
- Most 32-bit OSes by default limit file sizes to 2GB (and this may also apply to 32-bit builds on 64-bit OSes). This can often be worked around: `configure` selects suitable defines if this is possible. 64-bit builds have much larger limits.
- Because the pointers are larger, R’s basic structures are larger. This means that R objects take more space and (usually) more time to manipulate. So 64-bit builds of R will, all other things being equal, run slower than 32-bit builds.
- However, ‘other things’ may not be equal. In the specific case of ‘`x86_64`’ vs ‘`ix86`’, the 64-bit CPU has features (such as SSE2 instructions) which are guaranteed to be present but are optional on the 32-bit CPU, and also has more general-purpose registers. This means that on chips like a desktop Intel i7 the vanilla 64-bit version of R has been around 10% faster on both Linux and macOS. (Laptop CPUs are usually relatively slower in 64-bit mode.)

So, for speed you may want to use a 32-bit build (especially on a laptop), 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.

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). For example, each dimension of an array is limited to 2^{31} - 1.

## 9 The standalone Rmath library

The routines supporting the distribution and special44 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 `"4.3.2"`.

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

        ISNAN, R_FINITE, R_log, R_pow and R_pow_di

and (extern) constants `R_PosInf`, `R_NegInf` and `NA_REAL`.

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

        double unif_rand(void)

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

        set_seed(unsigned int, unsigned int)

to set its seeds).

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

    typedef enum {
        BUGGY_KINDERMAN_RAMAGE,
        AHRENS_DIETER,
        BOX_MULLER,
        USER_NORM,
        INVERSION,
        KINDERMAN_RAMAGE
    } N01type;

(and ‘`USER_NORM`’ is not available).

### 9.1 Unix-alikes

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

Then (in `src/nmath/standalone`)

    make

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

To use the routines in your own C or C++ programs, include

    #define MATHLIB_STANDALONE
    #include <Rmath.h>

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 (`libRmath.dylib`, `DYLD_FALLBACK_LIBRARY_PATH` on macOS).

The targets

    make install
    make uninstall

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.

‘`make install`’ installs a file for `pkg-config` to use by e.g.

    $(CC) `pkg-config --cflags libRmath` -c test.c
    $(CC) `pkg-config --libs libRmath` test.o -o test

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

### 9.2 Windows

You need to set up45 almost all the tools to make R and then run (in a Unix-like shell)

    (cd ../../gnuwin32; make MkRules)
    (cd ../../include; make -f Makefile.win config.h Rconfig.h Rmath.h)
    make -f Makefile.win

Alternatively, in a `cmd.exe` shell use

    cd ../../include
    make -f Makefile.win config.h Rconfig.h Rmath.h
    cd ../nmath/standalone
    make -f Makefile.win

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

    make -f Makefile.win shared implib

To use the routines in your own C or C++ programs using MinGW-w64, include

    #define MATHLIB_STANDALONE
    #include <Rmath.h>

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

    -Wl,-Bstatic -lRmath -Wl,Bdynamic
    -Wl,-Bdynamic -lRmath

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-w64 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++.

If you make use of dynamic linking you should use

    #define MATHLIB_STANDALONE
    #define RMATH_DLL
    #include <Rmath.h>

to ensure that the constants like `NA_REAL` are linked correctly. (Auto-import will probably work with MinGW-w64, 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 Debian/Ubuntu’s) 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 90 (see Using Fortran). Your C compiler should be ISO/IEC 6005946, POSIX 1003.1 and C99-compliant.47 R tries to choose suitable flags48 for the C compilers it knows about, but you may have to set `CC` or `CFLAGS` suitably. (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 macOS) you need ‘`X11`’ installed, including its headers and client libraries. For recent Fedora/RedHat distributions it means (at least) RPMs ‘`libX11`’, ‘`libX11-devel`’, ‘`libXt`’ and ‘`libXt-devel`’. On Debian/Ubuntu 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 (including its headers): version 6.0 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 by default for `glibc` 49 but not of most commercial Unixes. However, you can make use of GNU `libiconv` (as used on macOS: see https://www.gnu.org/software/libiconv/).

The OS needs to have enough support50 for wide-character types: this is checked at configuration. Some C99 functions51 are required and checked for at configuration. A small number of POSIX functions52 are essential, and others53 will be used if available.

Installations of `zlib` (version 1.2.5 or later), `libbz2` (version 1.0.6 or later: called bzip2-libs/bzip2-devel or libbz2-1.0/libbz2-dev by some Linux distributions) and `liblzma` 54 version 5.0.3 or later are required.

Either PCRE1 (version 8.32 or later, formerly known as just PCRE) or PCRE2 is required: PCRE2 is preferred and using PCRE1 requires `configure` option `--with-pcre1`. Only the 8-bit library and headers are needed if these are packaged separately. JIT support (optional) is desirable for the best performance. For PCRE2 >= 10.30 (which is desirable as matching has been re-written not to use recursion and the Unicode tables were updated to version 10)

    ./configure --enable-jit

suffices. If building PCRE1 for use with R a suitable `configure` command might be

    ./configure --enable-utf --enable-unicode-properties --enable-jit --disable-cpp

The `--enable-jit` flag is supported for most common CPUs but does not work (well or at all) for ‘`arm64`’ macOS.

Some packages require the ‘Unicode properties’ which are optional for PCRE1: support for this and JIT can be checked at run-time by calling `pcre_config()`.

Library `libcurl` (version 7.28.0 or later) is required. Information on `libcurl` is found from the `curl-config` script: if that is missing or needs to be overridden55 there are macros to do so described in file `config.site`.

A `tar` program is needed to unpack the sources and packages (including the recommended packages). A version56 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. (On NetBSD/OpenBSD systems set this to `bsdtar` if that is installed.)

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 `texi2any` version 5.1 or later installed (which requires `perl`), and if not most of the HTML manuals will be linked to a version on 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`.57 Further, the versions of `texi2dvi` and `texinfo.tex` need to be compatible: we have seen problems with older TeX distributions.

If you want to build from the R Subversion repository then `texi2any` is highly recommended as it is used to create files which are in the tarball but not stored in the Subversion repository.

The PDF documentation (including `doc/NEWS.pdf`) and building vignettes needs `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 kept up-to-date. A number of standard LaTeX packages are required for the PDF manuals (including url and some of the font packages such as times and helvetic and also amsfonts) and others such as hyperref and inconsolata are desirable (and without them you may need to change R’s defaults: see Making the manuals). Note that package hyperref (currently) requires packages kvoptions, ltxcmds and refcount, and inconsolata requires xkeyval. Building the base vignettes requires fancyvrb, natbib, parskip (which currently requires etoolbox) and listings. For distributions based on TeX Live the simplest approach may be to install collections collection-latex, collection-fontsrecommended, collection-latexrecommended, collection-fontsextra and collection-latexextra (assuming they are not installed by default): Fedora uses names like texlive-collection-fontsextra and Debian/Ubuntu like texlive-fonts-extra.

Programs `qpdf` and ghostscript (`gs`) are desirable as these will be used to compact the installed PDF vignettes and any PDF manuals.

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

For date-times to work correctly it is essential that the tables defining time zones are installed: these are usually in an OS component named something like `tzdata`. On most OSes they are required but installations of Alpine Linux have been seen without them. There is a `configure` check that recent date-times to work correctly in different time zones which catches this when installing from source (but not for binary distributions).

Those distributing binary versions of R may need to be aware of the licences of the external libraries it is linked to (including ‘useful’ libraries from the next section). The `liblzma` library is in the public domain and X11, `libbzip2`, `libcurl` and `zlib` have MIT-style licences. PCRE and PCRE2 have a BSD-style licence which requires distribution of the licence (included in R’s `COPYRIGHTS` file) in binary distributions. GNU `readline` is licensed under GPL (which version(s) of GPL depends on the `readline` version).

### 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 of the `gettext` runtime 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 Pango libraries. Cairo version 1.2.0 or later and Pango version 1.10 or later are required (but much later versions are current). R checks for `pkg-config`, and uses that to check first that the ‘`pangocairo`’ package is installed (and if not, ‘`cairo`’) then if suitable code can be compiled. These tests will fail if `pkg-config` is not installed58, and might fail if `cairo` was built statically unless `configure` option `--with-static-cairo` is used. Most systems with `Gtk+` 2.8 or later installed will have suitable libraries: for Fedora users the `pango-devel` RPM and its dependencies suffice. It is possible (but very unusual on a platform with X11) to build Cairo without its `cairo-xlib` module in which case `X11(type = "cairo")` will not be available. Pango is optional but highly desirable as it is likely to give much better text rendering, including kerning.

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` package59 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://pagure.io/liberation-fonts,60 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 (https://en.wikipedia.org/wiki/Liberation_fonts). Then there is the ‘Free UCS Outline Fonts’ project (https://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) and `zlib` or `libtiff` (versions 4.0.[5-10] and 4.[123].0 have been tested) respectively. `pkg-config` is used if available and so needs the appropriate `.pc` file (which requires `libtiff` version 4.x and is not available on all platforms for `jpeg` before version 9c). They also need support for either `X11` or `cairo` (see above). Should support for these devices not be required or broken system libraries need to be avoided there are `configure` options `--without-libpng`, `--without-jpeglib` and `--without-libtiff`. The TIFF library has many optional features such as `jpeg`, `libz`, `zstd`, `lzma`, `webp`, `jbig` and `jpeg12`, none of which is required for the `tiff()` devices but may need to be present to link the library (usually only an issue for static linking). `pkg-config` can tell you what other libraries are required for linking, for example by `pkg-config libtiff-4 --static --libs`.

Option `--with-system-tre` is also available: it needs a recent version of TRE. (The latest sources are in the `git` repository at https://github.com/laurikari/tre/, but at the time of writing the resulting build did not complete its checks, nor did R built against the version supplied by Fedora.)

An implementation of XDR is required, and the R sources contain one which is likely to suffice (although a system version may have higher performance). XDR is part of RPC and historically has been part of `libc` on a Unix-alike. (In principle `man xdr_string` should tell you which library is needed, but it often does not: on some OSes it is provided by `libnsl`.) However some builds61 of `glibc` omit or hide it with the intention that the TI-RPC library be used, in which case `libtirpc` (and its development version) should be installed, and its headers62 need to be on the C include path or under `/usr/include/tirpc`.

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 macOS 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, https://icu.unicode.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, FreeBSD, macOS and AIX, usually as `libicu` or `icu4c`. It will be used by default where available: should a very old or broken version of ICU be found this can be suppressed by `--without-ICU`.

The `bitmap` and `dev2bitmap` devices and function `embedFonts()` use ghostscript (https://www.ghostscript.com/). 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.

At the time of writing a full installation on Fedora Linux used the following packages and their development versions, and this may provide a useful checklist for other systems:

    bzip2 cairo fontconfig freetype fribidi gcc gcc-gfortran gcc-c++ glib2
    glibc harfbuzz lapack libX11 libXext libXt libcurl libicu
    libjpeg libpng libtiff libtirpc libxcrypt ncurses pango
    pkgconf-pkg-config pcre2 readline tcl tk xz zlib

plus, preferably a TeX installation and Java.

#### A.2.1 Tcl/Tk

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

`--with-tcltk`

  use Tcl/Tk, or specify its library directory

`--with-tcl-config=TCL_CONFIG`

  specify location of `tclConfig.sh`

`--with-tk-config=TK_CONFIG`

  specify location of `tkConfig.sh`

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 8.5.19 and 8.6.12 have been tested (including most versions of 8.4.x, but not recently).

Note that the `tk.h` header includes63 X11 headers, so you will need X11 and its development files installed.

#### A.2.2 Java support

The build process looks for Java support on the host system, and if it finds it sets some settings which are useful for Java-using packages (such as rJava and JavaGD: these require a full JDK). This check can be suppressed by configure option `--disable-java`. Configure variable `JAVA_HOME` can be set to point to a specific JRE/JDK, on the `configure` command line or in the environment.

Principal amongst these settings are some 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

    JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.322.b06-6.fc34.x86_64/jre
    R_JAVA_LD_LIBRARY_PATH=${JAVA_HOME}/lib/amd64/server

Unfortunately this 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` which updates settings in both `R_HOME/etc/Makeconf` and `R_HOME/etc/ldpaths`. See `R CMD javareconf --help` for details: note that this needs to be done by the account owning the R installation.

Another way of overriding those settings is to set the environment variable `R_JAVA_LD_LIBRARY_PATH` (before R is started, hence not in `~/.Renviron`), which suffices to run already-installed Java-using packages. For example

    R_JAVA_LD_LIBRARY_PATH=/usr/lib/jvm/java-1.8.0/jre/lib/amd64/server

It may be possible to avoid this by specifying an invariant link as the path when configuring. For example, on that system any of

    JAVA_HOME=/usr/lib/jvm/java
    JAVA_HOME=/usr/lib/jvm/java-1.8.0
    JAVA_HOME=/usr/lib/jvm/java-1.8.0/jre
    JAVA_HOME=/usr/lib/jvm/jre-1.8.0

worked (since the ‘auto’ setting of `/etc/alternatives` chose Java 8 aka 1.8.0).

‘Non-server’ Oracle distributions of Java as from version 11 are of a full JDK. However, Linux distributions can be confusing: for example Fedora 34 had

    java-1.8.0-openjdk
    java-1.8.0-openjdk-devel
    java-openjdk
    java-openjdk-devel
    java-11-openjdk
    java-11-openjdk-devel
    java-17-openjdk
    java-17-openjdk-devel
    java-latest-openjdk
    java-latest-openjdk-devel

where the `-devel` RPMs are needed to complete the JDK. Debian/Ubuntu use ‘`-jre`’ and ‘`-jdk`’, e.g.

    sudo apt install default-jdk

#### A.2.3 Other compiled languages

Some add-on packages need a C++ compiler. This is specified by the configure variables `CXX`, `CXXFLAGS` and similar. `configure` will normally find a suitable compiler. It is possible to specify an alternative C++17 compiler by the configure variables `CXX17`, `CXX17STD`, `CXX17FLAGS` and similar (see C++ Support). Again, `configure` will normally find a suitable value for `CXX17STD` if the compiler given by `CXX` is capable of compiling C++17 code, but it is possible that a completely different compiler will be needed. (Similar macros are provided for C++20.)

For source files with extension `.f90` or `.f95` containing free-form Fortran, the compiler defined by the macro `FC` is used by `R CMD INSTALL`. Note that it is detected by the name of the command without a test that it can actually compile Fortran 90 code. Set the configure variable `FC` to override this if necessary: variables `FCFLAGS` and `FCLIBS_XTRA` might also need to be set.

See file `config.site` in the R source for more details about these variables.

### A.3 Linear algebra

The linear algebra routines in R make use of BLAS (Basic Linear Algebra Subprograms, https://netlib.org/blas/faq.html) routines, and most make use of routines from LAPACK (Linear Algebra PACKage, https://netlib.org/lapack/). The R sources contain reference (Fortran) implementations of these, but they can be replaced by external libraries, usually those tuned for speed on specific CPUs. These libraries normally contain all of the BLAS routines and some tuned LAPACK routines and perhaps the rest of LAPACK from the reference implementation. Because of the way linking works, using an external BLAS library may necessitate using the version of LAPACK it contains.

Note that the alternative implementations will not give identical numeric results. Some differences may be benign (such the signs of SVDs and eigenvectors), but the optimized routines can be less accurate and (particularly for LAPACK) can be from older versions with fewer corrections. However, R relies on ISO/IEC 60559 compliance. 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`. The internal BLAS has been extensively patched to avoid this whereas MKL’s documentation has warned

> LAPACK routines assume that input matrices do not contain IEEE 754 special values such as INF or NaN values. Using these special values may cause LAPACK to return unexpected results or become unstable.

Some of the external libraries 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. On a machine running other tasks, there can be contention for CPU caches that reduces the effectiveness of the optimization of cache use by a BLAS implementation: some people warn that this is especially problematic for hyperthreaded CPUs.

BLAS and LAPACK routines may be used inside threaded code, for example in OpenMP sections in packages such as mgcv. The reference implementations are thread-safe but external ones may not be (even single-threaded ones): this can lead to hard-to-track-down incorrect results or segfaults.

There is a tendency for re-distributors of R to use ‘enhanced’ linear algebra libraries without explaining their downsides.

#### A.3.1 BLAS

An external BLAS library has to be explicitly requested at configure time.

You can specify a particular BLAS library via a value for the configuration option `--with-blas`. If this 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 suitable64 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

    --with-blas="foo"

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 (as of LAPACK 3.9.1: 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. Also, the BLAS can be switched after configure is run, either as a symbolic link or by the mechanisms mentioned below, and this can defeat the completeness check.

Some enhanced BLASes are compiler-system-specific (`Accelerate` on macOS, `sunperf` on Solaris65, `libessl` on IBM). The correct incantation for these is often found via `--with-blas` with no value on the appropriate platforms.

Note that under Unix (but not under Windows) if R is compiled against a non-default BLAS and `--enable-BLAS-shlib` is not used (it is the default on all platforms except AIX), 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.

Debian/Ubuntu systems provide a system-specific way to switch the BLAS in use: Build R with `--with-blas` to select the OS version of the reference BLAS, and then use `update-alternatives` to switch between the available BLAS libraries. See https://wiki.debian.org/DebianScience/LinearAlgebraLibraries.

Fedora 33 and later offer ‘FlexiBLAS’, a similar mechanism for switching the BLAS in use (https://www.mpi-magdeburg.mpg.de/projects/flexiblas). However, rather than overriding `libblas`, this requires configuring R with option `--with-blas=flexiblas`. ‘Backend’ wrappers are available for the reference BLAS, ATLAS and serial, threaded and OpenMP builds of OpenBLAS and BLIS. This can be controlled from a running R session by package flexiblas.

BLAS implementations which use parallel computations can be non-deterministic: this is known for ATLAS.

#### A.3.1.1 ATLAS

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

ATLAS contains replacements for a small number of LAPACK routines, but can be built to merge these with the reference LAPACK sources to include a full LAPACK library.

Recent versions of ATLAS can be built as a single shared library, either `libsatlas` or `libtatlas` (serial or threaded respectively): these may even contain a full LAPACK. Such builds can be used by one of

    --with-blas=satlas
    --with-blas=tatlas

or, as on ‘`x86_64`’ Fedora where a path needs to be specified,

    --with-blas="-L/usr/lib64/atlas -lsatlas"
    --with-blas="-L/usr/lib64/atlas -ltatlas"

Distributed ATLAS libraries cannot be tuned to your machine and so are a compromise: for example Fedora tunes66 ‘`x86_64`’ RPMs for CPUs with SSE3 extensions, and separate RPMs may be available for specific CPU families.

Note that building R on Linux against distributed shared libraries may need ‘`-devel`’ or ‘`-dev`’ packages installed.

Linking against multiple static libraries requires one of

    --with-blas="-lf77blas -latlas"
    --with-blas="-lptf77blas -lpthread -latlas"
    --with-blas="-L/path/to/ATLAS/libs -lf77blas -latlas"
    --with-blas="-L/path/to/ATLAS/libs -lptf77blas -lpthread -latlas"

Consult its installation guide67 for how to build ATLAS as a shared library or as a static library with position-independent code (on platforms where that matters).

According to the ATLAS FAQ68 the maximum number of threads used by multi-threaded ATLAS is set at compile time. Also, the author advises against using multi-threaded ATLAS on hyperthreaded CPUs without restricting affinities at compile-time to one virtual core per physical CPU. (For the Fedora libraries the compile-time flag specifies 4 threads.)

#### A.3.1.2 OpenBLAS and BLIS

Dr Kazushige Goto wrote a tuned BLAS for several processors and OSes, which was frozen in 2010. OpenBLAS (https://www.openblas.net/) is a descendant project with support for some later CPUs.

This can be used by configuring R with something like

    --with-blas="openblas"

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

Some platforms provide multiple builds of OpenBLAS: for example Fedora has RPMs69

    openblas
    openblas-threads
    openblas-openmp

providing shared libraries

    libopenblas.so
    libopenblasp.so
    libopenblaso.so

respectively, each of which can be used as a shared BLAS. For the second and third the number of threads is controlled by `OPENBLAS_NUM_THREADS` and `OMP_NUM_THREADS` (as usual for OpenMP) respectively.

These and their Debian equivalents contain a complete LAPACK implementation.

Note that building R on Linux against distributed libraries may need ‘`-devel`’ or ‘`-dev`’ packages installed.

For ‘`ix86`’ and ‘`x86_64`’ CPUs most distributed libraries contain several alternatives for different CPU microarchitectures with the choice being made at run time.

Another descendant project is BLIS (https://github.com/flame/blis). This has (in Fedora) shared libraries

    libblis.so
    libblisp.so
    libbliso.so

(`p` for ‘threads’, `o` for OpenMP as for OpenBLAS) which can also be used as a shared BLAS. The Fedora builds do not include LAPACK in the BLIS libraries.

#### A.3.1.3 Intel MKL

For Intel processors (and perhaps others) and some distributions of Linux, there is Intel’s Math Kernel Library70. You are encouraged to read the documentation which is installed with the library before attempting to link to MKL. This includes a ‘link line advisor’ which will suggest appropriate incantations: its use is recommended. Or see https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl-link-line-advisor.html#gs.vpt6qp (which at the time of writing selected the Intel library for linking with GCC).

There are also versions of MKL for macOS71 and Windows, but when these have been tried they did not work with the default compilers used for R on those platforms.

The following examples have been used with MKL versions 10.3 to 2023.2.0, for GCC compilers on ‘`x86_64`’ CPUs. (See also Intel compilers.)

To use a sequential version of MKL we used

    MKL_LIB_PATH=/path/to/intel_mkl/mkl/lib/intel64
    export LD_LIBRARY_PATH=$MKL_LIB_PATH
    MKL="-L${MKL_LIB_PATH} -lmkl_gf_lp64 -lmkl_core -lmkl_sequential"
    ./configure --with-blas="$MKL" --with-lapack

The option `--with-lapack` is used since MKL contains a tuned copy of LAPACK (often older than the current version) as well as the BLAS (see LAPACK), although this can be omitted.

Threaded MKL may be used by replacing the line defining the variable `MKL` by

    MKL="-L${MKL_LIB_PATH} -lmkl_gf_lp64 -lmkl_core \
         -lmkl_gnu_thread -dl -fopenmp"

R can also be linked against a single shared library, `libmkl_rt.so`, for both BLAS and LAPACK, but the correct OpenMP and MKL interface layer then has to be selected via environment variables. With 64-bit builds and the GCC compilers, we used

    export MKL_INTERFACE_LAYER=GNU,LP64
    export MKL_THREADING_LAYER=GNU

On Debian/Ubuntu, MKL is provided by package `intel-mkl-full` and one can set `libmkl_rt.so` as the system-wide implementation of both BLAS and LAPACK during installation of the package, so that also R installed from Debian/Ubuntu package `r-base` would use it. It is, however, still essential to set `MKL_INTERFACE_LAYER` and `MKL_THREADING_LAYER` before running R, otherwise MKL computations will produce incorrect results. R does not have to be rebuilt to use MKL, but `configure` includes tests which may discover some errors such as a failure to set the correct OpenMP and MKL interface layer.

Note that the Debian/Ubuntu distribution can be quite old (for example `2020.4` in mid-2023 when `2023.1` was current): this can be important for the LAPACK version included.

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`, and in recent versions seems to default to a sensible value for sole use of the machine. (Parallel MKL has not always passed `make check-all`, but did with MKL 2019.4 and later.)

MKL includes a partial implementation of FFTW3, which causes trouble for applications that require some of the FFTW3 functionality unsupported in MKL. Please see the MKL manuals for description of these limitations and for instructions on how to create a custom version of MKL which excludes the FFTW3 wrappers.

There is Intel documentation for building R with MKL at https://www.intel.com/content/www/us/en/developer/articles/technical/using-onemkl-with-r.html: that includes

    -Wl,--no-as-needed

which we have not found necessary.

#### A.3.1.4 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`.

This has both advantages and disadvantages.

- It saves space by having only a single copy of the BLAS routines, which is helpful if there is an external static BLAS (as used to be standard for ATLAS).
- There may be performance disadvantages in using a shared BLAS. Probably the most likely is when R’s internal BLAS is used and R is not built as a shared library, when it is possible to build the BLAS into `R.bin` (and `libR.a`) without using position-independent code. However, experiments showed that in many cases using a shared BLAS was as fast, provided high levels of compiler optimization are used.
- It is easy to change the BLAS without needing to re-install R and all the add-on packages, since all references to the BLAS go through `libRblas`, and that can be replaced. Note though that any dynamic libraries the replacement links to will need to be found by the linker: this may need the library path to be changed in `R_HOME/etc/ldpaths`.

Another option to change the BLAS in use is to symlink a single dynamic BLAS library to `R_HOME/lib/libRblas.so`. For example, just

    mv R_HOME/lib/libRblas.so R_HOME/lib/libRblas.so.keep
    ln -s /usr/lib64/libopenblasp.so.0 R_HOME/lib/libRblas.so

on ‘`x86_64`’ Fedora will change the BLAS used to multithreaded OpenBLAS. A similar link works for most versions of the OpenBLAS (provided the appropriate `lib` directory is in the run-time library path or `ld.so` cache). It can also be used for a single-library ATLAS, so on ‘`x86_64`’ Fedora either of

    ln -s /usr/lib64/atlas/libsatlas.so.3 R_HOME/lib/libRblas.so
    ln -s /usr/lib64/atlas/libtatlas.so.3 R_HOME/lib/libRblas.so

can be used with its distributed ATLAS libraries. (If you have the ‘`-devel`’ RPMs installed you can omit the `.0`/`.3`.)

Note that rebuilding or symlinking `libRblas.so` may not suffice if the intention is to use a modified LAPACK contained in an external BLAS: the latter could even cause conflicts. However, on Fedora where the OpenBLAS distribution contains a copy of LAPACK, it is the latter which is used.

#### A.3.2 LAPACK

If when configuring R a system LAPACK library is found of version 3.10.0 or later (and does not contain BLAS routines) it will be used instead of compiling the LAPACK code in the package sources. This can be prevented by configuring R with `--without-lapack`. Using a static `liblapack.a` is not supported.

It is assumed that `-llapack` is the reference LAPACK library but on Debian/Ubuntu it can be switched, including after R is installed. On such a platform it is better to use `--without-lapack` or `--with-blas --with-lapack` (see below) explicitly. The known examples72 of a non-reference LAPACK library found at installation all contain BLAS routines so are not used by a default `configure` run.

Provision is made for specifying an external LAPACK library with option `--with-lapack`, principally to cope with BLAS libraries which contain a copy of LAPACK (such as `Accelerate` on macOS and some builds of ATLAS, FlexiBLAS, MKL and OpenBLAS on ‘`ix86`’/‘`x86_64`’ Linux). At least LAPACK version 3.2 is required. This can only be done if `--with-blas` has been used.

However, the likely performance gains are thought to be small (and may be negative). 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` without a value. The default for `--with-lapack` is to check the BLAS library (for function `DPSTRF`) 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. Similarly, OpenBLAS can be built to contain an optimized subset of LAPACK or a full LAPACK (the latter seeming to be the default).

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 and the BLAS library does not contain LAPACK.

Please bear in mind that using `--with-lapack` is provided only because it is necessary on some platforms and because some users want to experiment with claimed performance improvements. In practice its main uses are without a value,

- with an ‘enhanced’ BLAS such as ATLAS, FlexiBLAS, MKL or OpenBLAS which contains a full LAPACK (to avoid possible conflicts), or
- on Debian/Ubuntu systems to select the system `liblapack` which can be switched by the ‘alternatives’ mechanism.

#### 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 Oracle compilers the flag `-dalign` is needed if `sunperf` is to be used.

On some systems it has been necessary that an external BLAS/LAPACK was built with the same Fortran compiler used to build R.

BLAS and LAPACK libraries built with recent versions of `gfortran` require calls from C/C++ to handle ‘hidden’ character lengths — R itself does so but many packages used not to and some have segfaulted. This was largely circumvented by using the Fortran flag `-fno-optimize-sibling-calls` (formerly set by `configure` if it detected `gfortran` 7 or later): however use of the R headers which include those character-length arguments is no longer optional in packages.

LAPACK 3.9.0 (and probably earlier) had a bug in which the DCOMBSSQ subroutine may cause NA to be interpreted as zero. This is fixed in the R 3.6.3 and later sources, but if you use an external LAPACK, you may need to fix it there. (The bug was corrected in 3.9.1 and the routine removed in 3.10.1.)

The code (in `dlapack.f`) should read

    *     ..
    *     .. Executable Statements ..
    *
          IF( V1( 1 ).GE.V2( 1 ) ) THEN
             IF( V1( 1 ).NE.ZERO ) THEN
                V1( 2 ) = V1( 2 ) + ( V2( 1 ) / V1( 1 ) )**2 * V2( 2 )
             ELSE
                V1( 2 ) = V1( 2 ) + V2( 2 )
             END IF
          ELSE
             V1( 2 ) = V2( 2 ) + ( V1( 1 ) / V2( 1 ) )**2 * V1( 2 )
             V1( 1 ) = V2( 1 )
          END IF
          RETURN

(The inner ELSE clause was missing in LAPACK 3.9.0.)

If you do use an external LAPACK, be aware of potential problems with other bugs in the LAPACK sources (or in the posted corrections to those sources), seen several times in Linux distributions over the years. We have even seen distributions with missing LAPACK routines from their `liblapack`.

We rely on limited support in LAPACK for matrices with 2^{31} or more elements: it is possible that an external LAPACK will not have that support.

## Appendix B Configuration on a Unix-alike

### B.1 Configuration options

`configure` has many options: running

    ./configure --help

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

`--with-x`

  use the X Window System [yes]

`--x-includes=DIR`

  X include files are in DIR

`--x-libraries=DIR`

  X library files are in DIR

`--with-readline`

  use readline library (if available) [yes]

`--enable-R-profiling`

  attempt to compile support for `Rprof()` [yes]

`--enable-memory-profiling`

  attempt to compile support for `Rprofmem()` and `tracemem()` [no]

`--enable-R-shlib`

  build R as a shared/dynamic library [no]

`--enable-BLAS-shlib`

  build the BLAS as a shared/dynamic library [yes, except on AIX]

You can use `--without-foo` or `--disable-foo` for the negatives.

You will want to use `--disable-R-profiling` if you are building a profiled executable of R (e.g. with ‘`-pg)`’. Support for R profiling requires OS support for POSIX threads (aka ‘`pthreads`’), which are available on all mainstream Unix-alike platforms.

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 performance73 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.

For maximally effective use of `valgrind`, R should be compiled with valgrind instrumentation. The `configure` option is `--with-valgrind-instrumentation=level`, where level is 0, 1 or 2. (Level 0 is the default and does not add anything.) The system headers for `valgrind` will be used if present (on Linux they may be in a separate package such as valgrind-devel). Note though that there is no guarantee that the code in R will be compatible with very old74 or future `valgrind` headers.

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

The `configure` script has other generic options added by `autoconf` and which are not supported for R: in particular building for one architecture on a different host is not possible.

### B.2 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

      Natural language support but running in an English locale

in the greeting on starting R.

### B.3 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

    ./configure VAR=value

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`, 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.3.1 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 program `paperconf` is found, present in many Linux distributions, or the environment variable `PAPERSIZE` is set, these are used to produce the default.)

#### B.3.2 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.

Its counterpart for PDF files is `R_PDFVIEWER`.

#### B.3.3 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`, but note that on most systems `/usr/local/include` is regarded as a system include directory and so instances in that macro will be skipped) 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. 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`, but may result in a less reliable build (both segfaults and incorrect numeric computations have been seen). 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 https://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.3.4 Making manuals

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

### B.4 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.5 Using make

To build in a separate directory you need a `make` that supports the `VPATH` variable, for example GNU `make` and `dmake`.

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

    ./configure MAKE=gmake

### B.6 Using Fortran

To compile R, you need a Fortran 90 compiler. The current default is to search for `gfortran`, `g95`, `xlf95` `f95`, `fort`, `ifort`, `ifc`, `efc`, `pgfortran`, `pgf95` `lf95`, `ftn`, `nagfor`, `xlf90`, `f90`, `pgf90`, `pghpf`, `epcf90`. (Note that these are searched for by name, without checking the standard of Fortran they support.) The command and flags used should support fixed-form Fortran with extension `.f`: in the unusual case that a specific flag is needed for free-form Fortran with extension `.f90` or `.f95`, this can be specified as part of `FCFLAGS`.

The search mechanism can be changed using the configure variable `FC` which specifies the command that runs the Fortran 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 `FC` 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 `DOUBLE COMPLEX` and `COMPLEX*16` variables. This is checked for at configure time, as well as its equivalence to the `Rcomplex` C structure defined in `R_ext/Complex.h`.

`gfortran` 10 by default gives a compilation error for the previously widespread practice of passing a Fortran array element where an array is expected, or a scalar instead of a length-one array. See https://gcc.gnu.org/gcc-10/porting_to.html. `gfortran` 12 errors in more cases of this.

### B.7 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

`CPPFLAGS`

  header file search directory (`-I`) and any other miscellaneous options for the C and C++ preprocessors and compilers

`LDFLAGS`

  path (`-L`), stripping (`-s`) and any other miscellaneous options for the linker

and others include

`CFLAGS`

  debugging and optimization flags, C

`MAIN_CFLAGS`

  ditto, for compiling the main program (e.g. when profiling)

`SHLIB_CFLAGS`

  for shared objects (no known examples)

`FFLAGS`

  debugging and optimization flags, fixed-form Fortran

`FCFLAGS`

  debugging and optimization flags, free-form Fortran

`SAFE_FFLAGS`

  ditto for source files which need exact floating point behaviour

`MAIN_FFLAGS`

  ditto, for compiling the main program (e.g. when profiling)

`SHLIB_FFLAGS`

  for shared objects (no known examples)

`MAIN_LDFLAGS`

  additional flags for the main link

`SHLIB_LDFLAGS`

  additional flags for linking the shared objects

`LIBnn`

  the primary library directory, `lib` or `lib64`

`CPICFLAGS`

  special flags for compiling C code to be turned into a shared object

`FPICFLAGS`

  special flags for compiling Fortran code to be turned into a shared object

`CXXPICFLAGS`

  special flags for compiling C++ code to be turned into a shared object

`DEFS`

  defines to be used when compiling C code in R itself

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.

Other variables often set by `configure` include ‘`MAIN_LDFLAGS`’, ‘`SAFE_FFLAGS`’, ‘`SHLIB_LDFLAGS`’ and ‘`SHLIB_CXXLDFLAGS`’: see file `config.site` in the sources for more documentation on these and others.

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` and `LIBS` in `R_XTRA_CFLAGS` (and so on). These are for options which are always required, for example to force IEC 60559 compliance.

### B.8 Maintainer mode

There are several files that are part of the R sources but can be re-generated from their own sources by configuring with option `--enable-maintainer-mode` and then running `make` in the build directory. This requires other tools to be installed, discussed in the rest of this section.

File `configure` is created from `configure.ac` and the files under `m4` by `autoconf` and `aclocal` (part of the automake package). There is a formal version requirement on `autoconf` of 2.69 or later, but it is unlikely that anything other than the most recent versions75 have been thoroughly tested.

File `src/include/config.h` is created by `autoheader` (part of autoconf).

Grammar files `*.y` are converted to C sources by an implementation of `yacc`, usually `bison -y`: these are found in `src/main` and `src/library/tools/src`. It is known that earlier versions of `bison` generate code which reads (and in some cases writes) outside array bounds: `bison` 2.6.1 was found to be satisfactory.

The ultimate sources for package compiler are in its `noweb` directory. To re-create the sources from `src/library/compiler/noweb/compiler.nw`, the command `notangle` is required. Some Linux distributions include this command in package noweb. It can also be installed from the sources at https://www.cs.tufts.edu/~nr/noweb/76. The package sources are only re-created even in maintainer mode if `src/library/compiler/noweb/compiler.nw` has been updated.

## 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 contain notes on platforms such as HP-UX, IRIX, Alpha/OSF1 (for R < 2.10.0, and support has since been removed for all of these) and AIX (for R < = 3.5.x) for which we have had no recent reports.

C macros to select particular platforms can be tricky to track down (there is a fair amount of misinformation on the Web). The Wiki (currently) at https://sourceforge.net/p/predef/wiki/Home/ can be helpful. The R sources have used (often in included software under `src/extra`)

    AIX: _AIX
    Cygwin: __CYGWIN__
    FreeBSD: __FreeBSD__
    HP-UX: __hpux__, __hpux
    IRIX: sgi, __sgi
    Linux: __linux__
    macOS: __APPLE__
    NetBSD: __NetBSD__
    OpenBSD: __OpenBSD__
    Windows: _WIN32, _WIN64

Identifying compilers can be very tricky. GCC defines `__GNUC__`, but so do other compilers claiming conformance with it, notably (LLVM and Apple) `clang` and Intel compilers. Further, some use the value of `__GNUC__` for their version, not the version of GCC they claim to be compatible with.77 `clang`-based compilers define `__clang__`. Both LLVM and Apple `clang` define `__clang_major__` as a string giving their major version, but for example Apple’s 13.x.y is very different from LLVM’s 13.x.y. And compilers based on LLVM `clang`, for example from Intel and IBM, will define these. Some of the included software uses `__APPLE_CC__` to identify an Apple compiler (which used to include Apple builds of GCC), but Apple `clang` is better identified by the `__apple_build_version__` macro.

### C.1 X11 issues

The ‘`X11()`’ graphics device is the one started automatically on Unix-alikes (except most macOS builds) 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 reporting78 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

    xorg-x11-fonts-75dpi
    xorg-x11-fonts-100dpi
    xorg-x11-fonts-ISO8859-2-75dpi
    xorg-x11-fonts-Type1
    xorg-x11-fonts-cyrillic

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

    "-adobe-helvetica-%s-%s-*-*-%d-*-*-*-*-*-*-*"

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,

    /usr/share/fonts/default/Type1
    /usr/share/fonts/ja/TrueType

### C.2 Linux

Linux is the main development platform for R, so compilation from the sources is normally straightforward with the most common compilers and libraries.79

This section is about the GCC compilers: `gcc`/`gfortran`/`g++`.

Recall 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).) You should expect to see in the `configure` summary

      Interfaces supported:      X11, tcltk
      External libraries:        pcre2, readline, curl
      Additional capabilities:   PNG, JPEG, TIFF, NLS, cairo, ICU

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: one possibility is to add `-mtune=native` for the best possible performance on the machine on which R is being installed. 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.

Do not use `-O3` with `gcc` 11.0 or 11.1: it mis-compiles code resulting in plausible but incorrect results. (This was seen in package MASS but has been worked around there as from version 3.1-57.)

For platforms with both 64- and 32-bit support, it is likely that

    LDFLAGS="-L/usr/local/lib64 -L/usr/local/lib"

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 34 we used

    CC="gcc -m32"
    CXX="g++ -m32"
    FC="gfortran -m32"
    OBJC=${CC}
    LDFLAGS="-L/usr/local/lib"
    LIBnn=lib

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

    export PKG_CONFIG_PATH=/usr/local/lib/pkgconfig:/usr/lib/pkgconfig

The 32-bit system `libcurl` did not work with the system CA certificates: this is worked around in R’s test suite.

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

Note that some distributions of 32-bit `glibc` use a 32-bit `time_t` type, so to pass all the date-time checks needs R built with flag `--with-internal-tzcode`.

Users of ‘`ix86`’ CPUs with SSE2 support80 may prefer to use the C/C++/Fortran flags

    -mfpmath=sse -msse2

to force floating-point to use the same instructions as ‘`x86_64`’ builds and hence not make use of 80-bit ‘extended precision’ intermediate results. (NB: this affects more than floating-point operations. For some OSes and versions of `gcc` it might be necessary to add `-mstackrealign`.)

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

    CC="gcc -m64"
    CXX="gxx -m64"
    FC="gfortran -m64"
    CFLAGS="-mminimal-toc -fno-optimize-sibling-calls -g -O2"
    FFLAGS="-mminimal-toc -fno-optimize-sibling-calls -g -O2"

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

The setting of the macro ‘`SAFE_FFLAGS`’ may need some help. It should not need additional flags on platforms other than ‘`68000`’ (not likely to be encountered) and ‘`ix86`’. For the latter, if the Fortran compiler is GNU (`gfortran` or possibly `g77`) the flags

    -msse2 -mfpmath=sse

are added: earlier versions of R added `-ffloat-store` and this might still be needed if a ‘`ix86`’ CPU is encountered without SSE2 support. Note that it is a replacement for ‘`FFLAGS`’, so should include all the flags in that macro (except perhaps the optimization level).

Additional compilation flags can be specified for added safety/security checks. For example Fedora adds

    -Werror=format-security -Wp,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS
    -Fexceptions -fstack-protector-strong -fasynchronous-unwind-tables
    -fstack-clash-protection -fcf-protection

to all the C, C++ and Fortran compiler flags (even though `_GLIBCXX_ASSERTIONS` is only for C++ in current GCC and `glibc` and none of these are documented for `gfortran`). Use of `_GLIBCXX_ASSERTIONS` will link `abort` and `printf` into almost all C++ code, and `R CMD check --as-cran` will warn.

#### C.2.1 Clang

R has been built with Linux ‘`ix86`’ and ‘`x86_64`’ C and C++ compilers (https://clang.llvm.org) 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.

This has to be used in conjunction with a Fortran compiler: the `configure` code will remove `-lgcc` from `FLIBS`, which is needed for some versions of `gfortran`.

The current out-of-the-box default for `clang++` is to use the C++ runtime from the installed `g++`. Using the runtime from the `libc++` project (Fedora RPM `libcxx-devel`) via `-stdlib=libc++` has also been tested.

Recent versions have (optional when built) OpenMP support.81

There are problems mixing `clang` 15.0.0 and later built as default on Linux to produce PIE code and `gfortran` 11 or later, which does not. One symptom is that `configure` does not detect `FC_LEN_T`, which can be overcome by setting

    FPIEFLAGS=-fPIE

in `config.site`. (As from R 4.2.2 `configure` tries that value if it is unset.)

#### C.2.2 flang

The name `flang` has been used for two projects: this is about the sub-project of LLVM which builds a Fortran compiler and runtime libraries. The compiler is currently named `flang-new` but has been announced to be renamed to `flang` when more nearly complete (and at some earlier point in its development was known as `f18`).

The version in LLVM 16 was able to build R on ‘`x86_64`’ Linux with

    FC=/path/to/flang-new

with the matching `clang` used as the C compiler, and the build passed `make check-all`. There is also support for ‘`aarch64`’ and ‘`ppc64le`’ Linux, but these have not been tested with R.

#### C.2.3 Intel compilers

In late 2020 Intel revamped their C/C++ compilers (and later their Fortran compiler) to use an LLVM back-end (and for the C/C++ compilers, a modified version of `clang` as the front-end). Those compilers are only for ‘`x86_64`’: the earlier compilers (now branded ‘Classic’) also supported ‘`ix86`’ and 32-bit builds on ‘`x86_64`’.

The compilers are now all under Intel’s ‘oneAPI’ brand. The revamped ones are `icx`, `icpx` and `ifx`; they are identified by the C/C++ macro `__INTEL_LLVM_COMPILER` (and do not define `__INTEL_COMPILER`: they also define `__clang__` and `__clang_major__`).

The C++ compiler uses the system’s `lidstdc++` as its runtime library rather than LLVM’s `libc++`.

Standalone installers (which are free-of-charge) are available from https://www.intel.com/content/www/us/en/developer/articles/tool/oneapi-standalone-components.html: they are also part of the oneAPI Base and HPC (for Fortran) ToolKits.

We tried the LLVM-based compilers in oneAPI 2024.0.2 using (the paths do differ by compiler version)

    IP=/path/to/compilers/bin/
    CC=$IP/icx
    CXX=$IP/icpx
    FC=$IP/ifx
    CFLAGS="-O3 -fp-model precise -Wall -Wstrict-prototypes"
    C17FLAGS="-O3 -fp-model precise -Wall -Wno-strict-prototypes"
    FFLAGS="-O3 -fp-model precise -warn all,noexternals"
    FCFLAGS="-free -O3 -fp-model precise -warn all,noexternals"
    CXXFLAGS="-O3 -fp-model precise -Wall"
    LDFLAGS="-L/path/to/compilers/compiler/lib -L/usr/local/lib64"

but the build segfaulted in the checks (in complex arithmetic in `tests/lapack.R`).

Intel document building R with MKL: for the Intel compilers this needed something like

    MKL_LIB_PATH=/path/to/intel_mkl/mkl/lib/intel64
    export LD_LIBRARY_PATH="$MKL_LIB_PATH"
    MKL="-L${MKL_LIB_PATH} -lmkl_intel_lp64 -lmkl_core -lmkl_sequential"
    ./configure --with-blas="$MKL" --with-lapack

and the build passed its checks with MKL 2023.2.0 (but not 2024.0 on the hardware tested). It may also be possible to use a compiler option like `-qmkl=sequential`.

One quirk is that the Intel Fortran compilers do not accept `.f95` files, only `.f90`, for free-format Fortran. `configure` adds `-Tf` which tells the compiler this is indeed a Fortran file (and needs to immediately precede the file name), but `-free` is needed to say it is free-format. Hence setting the `FCFLAGS` macro.

The compilers have many options: as the C/C++ and Fortran compilers have different origins for their front-ends, there is little consistency in their options. (The C/C++ compilers support ‘all’ `clang` options even if undocumented for `icx`/`icpc`, such as `-Wno-strict-prototypes` above, However it is unclear for which version of `clang`: the Intel manual suggests checking `icx -help`.) The C/C++ compilers support clang-style LTO: it is not clear if the Fortran one does.

For some versions, including 2023.2.0, all CPU times in e.g. `proc.time()` are reported as zero unless `src/unix/sys-unix.c` is compiled with `-O0`.

The preferred Fortran standard for `ifx` can be set by one of `-std90`, `-std95`, `-std03`, `-std08` or `-std18` (and variants). However, this is documented to only affect warnings on non-standard features: the default is no such warnings.

Warning to package maintainers: the Intel Fortran compilers interpret comments intended for Visual Fortran82 like

    !DEC$ ATTRIBUTES DLLEXPORT,C,REFERENCE,ALIAS:'kdenestmlcvb' :: kdenestmlcvb

The `DLLEXPORT` gives a warning but the remainder silently generates incorrectly named entry points. Such comment lines need to be removed from code for use with R (even if using Intel Fortran on Windows).

#### C.2.3.1 ‘Classic’ Intel compilers

The classic compilers were `icc`, `icpc` and `ifort`. They are identified by the C/C++ macro `__INTEL_COMPILER`.

The classic C/C++ compilers remained available until October 2023. Version 2021.10.0 (shipped as part of oneAPI 2023.2.0) was tested in July 2023 using

    IP=/path/to/compilers/bin/intel64
    CC=$IP/icc
    CXX=$IP/icpc
    FC=$IP/ifort
    CFLAGS="-O3 -ip -fp-model precise"
    FFLAGS="-O3 -fp-model precise"
    FCFLAGS="-free -O3 -fp-model precise"
    CXXFLAGS="-O3  -fp-model precise"
    LDFLAGS="-L/path/to/compilers/compiler/lib/intel64_lin -L/usr/local/lib64"

but also segfaulted in the checks unless MKL was used. (CPU timings work with this compiler.)

To suppress endless warnings about deprecation, use

    CC="$IP/icc -diag-disable=10441"

`icpc` does not support C++23.

There has been only one other recent report on the use of these compilers: the rest of this section is left in case it provides helpful hints for people using them while they are still available.

Brian Ripley used version 9.0 of the compilers for ‘`x86_64`’ on Fedora Core 5 with

    CC=icc
    CFLAGS="-g -O3 -wd188 -ip -mp"
    FC=ifort
    FLAGS="-g -O3 -mp"
    CXX=icpc
    CXXFLAGS="-g -O3 -mp"
    ICC_LIBS=/opt/compilers/intel/cce/9.1.039/lib
    IFC_LIBS=/opt/compilers/intel/fce/9.1.033/lib
    LDFLAGS="-L$ICC_LIBS -L$IFC_LIBS -L/usr/local/lib64"
    SHLIB_CXXLD=icpc

It may be necessary to use `CC="icc -std=c99"` or `CC="icc -c99"` for C99-compliance. 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.

Others have reported success with versions 10.x and 11.x. Bjørn-Helge Mevik reported success with version 2015.3 of the compilers, using (for a SandyBridge CPU on Centos 6.x)

    fast="-fp-model precise -ip -O3 -opt-mem-layout-trans=3 -xHost -mavx"
    CC=icc
    CFLAGS="$fast -wd188"
    FC=ifort
    FFLAGS="$fast"
    CXX=icpc
    CXXFLAGS="$fast"

It is possible that 32-builds need to force the use of SSE2 instructions in `SAFE_FFLAGS`, e.g. by

    SAFE_FFLAGS=-axsse2

### C.3 macOS

The instructions here are for Intel 64-bit (‘`x86_64`’) or ‘Apple Silicon’ (‘`arm64`’) builds on macOS 11 (Big Sur), 12 (Monterey) and 13 (Ventura). (They may well work on Intel macOS 10.14 or 10.15, but are untested there.)

#### C.3.1 Prerequisites

The Intel components install into `/opt/R/x86_64`, the Apple silicon ones into `/opt/R/arm64`. This may not exist83 so it is simplest to first create the directory and adjust its ownership if desired: for example by

    sudo mkdir -p /opt/R/arm64
    sudo chown -R $USER /opt/R

Also, add `/opt/R/x86_64/bin` or `/opt/R/arm64/bin` to your path.

Define an appropriate variable in your Terminal:

    set LOCAL=/opt/R/x86_64 # Intel
    set LOCAL=/opt/R/arm64  # Apple Silicon

to use the code snippets here.

The following are essential to build R:

- Apple’s ‘Command Line Tools’: these can be (re-)installed by running `xcode-select --install` in a terminal.

  If you have a fresh OS installation, running e.g. `make` in a terminal will offer the installation of the command-line tools. If you have installed Xcode, this provides the command-line tools. The tools may need to be reinstalled when macOS is upgraded, as upgrading may partially or completely remove them.

  The Command Line Tools provide C and C++ compilers derived from LLVM’s `clang` but nowadays known as ‘Apple clang’ with different versioning (so Apple clang 14 is unrelated to LLVM clang 14).

- A Fortran compiler. See Fortran compiler.
- Binary components `pcre2` 84 and `xz` (for `liblzma`) from https://mac.r-project.org/bin/. There is an R script there to help with installing all the needed components. (At the time of writing `install.libs("r-base-dev")` installed neither `readline5` nor those needed to support Pango.)

  Intel users want the `darwin20` components: the `darwin17` ones are for macOS 10.13–10.15.

  Or this can be done manually, by for example

      curl -OL https://mac.r-project.org/bin/darwin20/x86_64/pcre2-10.42-darwin.20-x86_64.tar.xz
      sudo tar -xvzf pcre2-10.42-darwin.20-x86_64.tar.gz -C /
      curl -OL https://mac.r-project.org/bin/darwin20/x86_64/xz-5.4.2-darwin.20-x86_64.tar.xz
      sudo tar -xvzf xz-5.4.2-darwin.20-x86_64.tar.xz -C /

  (`sudo` is not needed if your account owns `/opt/R/x86_64` or `/opt/R/arm64` as appropriate.)

  Messages like ‘`opt/R/: Can't restore time`’ should be ignored.

and desirable

- Component `readline5`.85 If `readline` is not present, the emulation in Apple’s version of `libedit` (aka `editline`) will be used: if you wish to avoid that, configure with `--without-readline`.
- Components `jpeg`, `libpng`, `pkgconfig`, `tiff` and `zlib-system-stub` from https://mac.r-project.org/bin// for the full range of bitmapped graphics devices. (Some builds of `tiff` may require `libwebp` and/or `openjpeg`.)
- An X sub-system unless configuring using `--without-x`: see https://www.xquartz.org/. R’s `configure` script can be told to look for `X11` in XQuartz’s main location of `/opt/X11`, e.g. by

      --x-includes=/opt/X11/include --x-libraries=/opt/X11/lib

  Be wary of pre-release versions of XQuartz, which may be offered as an update.

- An Objective-C compiler, as provided by `clang` in the Command Line Tools: this is needed for the `quartz()` graphics device.

  Use `--without-aqua` if you want a standard Unix-alike build: apart from disabling `quartz()` and the ability to use the build with R.APP, it also changes the default location of the personal library (see `?.libPaths`).

- A Tcl/Tk installation, See Tcl/Tk headers and libraries.
- Support for Cairo-based graphics devices. See Cairo graphics.
- A TeX installation. See Other libraries.
- `texi2any` from a ‘`texinfo`’ distribution, which requires `perl` (currently a default part of macOS but it has been announced that it may not be in future). A version of `texi2any` has been included in the binary distribution of R and there is a `texinfo` component at https://mac.r-project.org/bin/.

To build R itself from the sources with the C/C++ compilers in the Command Line Tools (or Xcode) and `gfortran` from the installer mentioned below, use a file `config.site` containing

    CC=clang
    OBJC=$CC
    FC="/opt/gfortran/bin/gfortran -mtune=native"
    CPPFLAGS='-isystem $LOCAL/include'
    CXX=clang++

and configure by something like

    ./configure -C \
    --enable-R-shlib --enable-memory-profiling \
    --x-includes=/opt/X11/include --x-libraries=/opt/X11/lib \
    --with-tcl-config=$LOCAL/lib/tclConfig.sh \
    --with-tk-config=$LOCAL/lib/tkConfig.sh \
    PKG_CONFIG_PATH=$LOCAL/lib/pkgconfig:/usr/lib/pkgconfig

(See below for other options for Tcl/Tk.) For an ‘`arm64`’ build further flags are desirable in `config.site`:

    CFLAGS="-falign-functions=8 -g -O2"
    FFLAGS="-g -O2 -mmacos-version-min=11.0"
    FCFLAGS="-g -O2 -mmacos-version-min=11.0"

(the first flag in `CFLAGS` is needed to inter-work with the `gfortran` without segfaulting in some packages, and some builds of `gfortran` have targetted the current version of macOS (unlike `clang`, causing linker warnings).

To install packages using compiled code one needs the Command Line Tools (or Xcode) and appropriate compilers, e.g. the C/C++ compilers from those tools and/or `gfortran`. Some packages have further requirements such as component `pkgconfig` (and to set `PKG_CONFIG_PATH=` as above).

A subversion client can be obtained from https://mac.r-project.org/tools/, for example by

    curl -OL https://mac.r-project.org/tools/subversion-1.14.0-darwin15.6.tar.gz
    tar xf subversion-1.14.0-darwin15.6.tar.gz
    sudo cp subversion-1.14.0-darwin15.6/svn $LOCAL/bin

(There also an `arm64` version on that web page.)

If building software or installing source packages with `cmake` (or a non-Apple `make`) for ‘Apple Silicon’ ensure it contains the ‘`arm64`’ architecture (use `file` to be sure). Running Apple compilers from an ‘`x86_64`’ executable will generate ‘`x86_64`’ code ….

Updating an ‘`arm64`’ build may fail because of the bug described at https://openradar.appspot.com/FB8914243 but ab initio builds work. This has been far rarer since macOS 13.

If you are using the macOS 13 SDK 86, you may need to add something like `-mmacos-version-min=12.0` to ‘`CFLAGS`’.

Linker warnings like

    ld: warning: could not create compact unwind for _sort_:
       register 26 saved somewhere other than in frame
    ld: warning: ld: warning:
       could not create compact unwind for _arcoef_: registers 23 and 24 not saved contiguously in frame
    ld: warning: could not create compact unwind for ___emutls_get_address:
       registers 23 and 24 not saved contiguously in frame

can be ignored. These stem from compiled Fortran code, including its run-time libraries.

The default security settings can make it difficult to install Apple packages which have not been ‘notarized’87 by Apple. And not just packages, as this has been seen for executables contained in tarballs/zipfiles (for example, for `pandoc`). Usually one can use ‘`Open With`’ (Control/right/two-finger-click in Finder), then select ‘`Installer`’ and ‘`Open`’ if you get a further warning message.

If you run into problems with ‘quarantine’ for tarballs downloaded in a browser, consider using `curl -OL` to download (as illustrated above) or `xattr -c` to remove extended attributes.

`configure` defaults to `--with-internal-tzcode` on macOS. The native implementation used to be unusable on earlier versions (with a 32-bit `time_t` and/or timezone tables missing information beyond the 32-bit range). For, e.g., macOS 12.6, option `--without-internal-tzcode` can be used to override this and R contains sufficient workarounds (for example, the native code fails to recognize dates with a negative `tm_year`, that is dates before 1900) for R to pass its checks. However, there are discrepancies, notably in Europe in the 1900s and 1940s, even though the Olson database contains the correct information.

#### C.3.2 Fortran compiler

There is ‘universal’ (Intel and `arm64`) build of `gfortran` 12.2 at https://mac.r-project.org/tools/gfortran-12.2-universal.pkg. This installs into `/opt/gfortran`.

The `/opt/gfortran/SDK` symlink should point to the desired path to the SDK (defaults to the command line tools SDK). This can be updated by running `/opt/gfortran/bin/gfortran-update-sdk` or manually. If the symlink is broken, the driver will issue a warning and use `xcrun -show-sdk-path` to try to find an SDK and use its path. (The SDK path is used when using `gfortran` to link, so not when building R but when installing a few packages.)

#### C.3.3 Cairo graphics

Cairo-based graphics devices such as `cairo_ps`, `cairo_pdf`, `X11(type = "cairo")` and the Cairo-based types of devices `bmp` `jpeg`, `png` and `tiff` are not the default on macOS, and much less used than the Quartz-based devices. However, the only SVG device in the R distribution, `svg`, is based on Cairo.

Support for Cairo is optional and can be added in several ways, all of which need `pkg-config`. `configure` will add Cairo support if `pkg-config` finds package `cairo` unless `--without-cairo` is used.

A way to statically link Cairo is by downloading and unpacking components `cairo`, `fontconfig`, `freetype`, `pixman` and `zlib-system-stub` (and do not have `/opt/X11/lib/pkgconfig` in `PKG_CONFIG_PATH`). Some static builds of `fontconfig` need `libxml2` (from component `xml2`) and others `expat`, supplied by macOS but needing a file `$LOCAL/lib/pkgconfig/expat.pc` along the lines of

    Name: expat
    Version: 2.2.8
    Description: expat XML parser
    URL: http://www.libexpat.org
    Libs: -lexpat
    Cflags:

Note that the list of components is liable to change: running `pkg-config cairo --exists --print-errors` should tell you if any others are required.

The best font experience of Cairo graphics will be to use it in combination with Pango which will match that supported on most other Unix-alikes. `configure` uses `pkg-config` to determine if all the external software required by both Pango and Cairo is available: running `pkg-config pangocairo --exists --print-errors` should show if the installation suffices and if not, what is missing. At the time of writing using pre-built components `cairo`, `fontconfig`, `freetype`, `ffi`, `fribidi`, `gettext`, `icu`, `glib`, `harfbuzz`, `pango`, `pcre`, `pixman` and `xml2` sufficed.

#### C.3.4 Other C/C++ compilers

Other distributions of `clang` may be available from https://github.com/llvm/llvm-project/releases/ (recently only for `arm64` and usually unsigned/not notarized which makes them hard to use). In particular, these include support for OpenMP which Apple `clang` does not. Some of these have included support for the ASAN and UBSAN sanitizers.

Suppose one of these distributions is installed under `$LOCAL/llvm`. Use a file `config.site` containing

    CC="$LOCAL/llvm/bin/clang -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk"
    CXX="$LOCAL/llvm/bin/clang++ -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk"
    OBJC=$CC
    FC=$LOCAL/gfortran/bin/gfortran
    LDFLAGS="-L$LOCAL/llvm/lib -L$LOCAL/lib"
    R_LD_LIBRARY_PATH=$LOCAL/llvm/lib:$LOCAL/lib

Should the location of the SDK change (or where Xcode provides the SDK rather than the Command Line Tools), it can be found by running `xcrun -show-sdk-path`.

The care to specify library paths is to ensure that the OpenMP runtime library, here `$LOCAL/llvm/lib/libomp.dylib`, is found when needed. If this works, you should see the line

    checking whether OpenMP SIMD reduction is supported... yes

in the `configure` output. Also, ‘`R_LD_LIBRARY_PATH`’ needs to be set to find the latest version of the C++ run-time libraries rather than the system ones.

It is usually possible to build R with GCC (built from the sources, from a `gfortran` distribution, from Homebrew, …). When last tested88 it was not possible to use `gcc` to build the `quartz()` device, so `configure --without-aqua` may be required.

It is usually possible to add some OpenMP support to the Apple `clang` compilers: see https://mac.r-project.org/openmp/. Note that that approach is somewhat fragile as it needs a `libomp.dylib` library matching the version of the compiler used—and for example at the time of writing none was offered for the current compilers in Xcode/CLT 14.3 nor 15.

#### C.3.5 Other libraries

Pre-compiled versions of many of the Useful libraries and programs are available from https://mac.r-project.org/bin//.

The `Accelerate` library89 can be used via the configuration option

    --with-blas="-framework Accelerate"

to provide potentially higher-performance versions of the BLAS and LAPACK routines.90 his also includes a full LAPACK which can be used via `--with-lapack`: however, the version of LAPACK it contains has often been seriously old (and is not used unless `--with-lapack` is specified). Some CRAN builds of R can be switched91 to use Accelerate’s BLAS.

Support for the version of Accelerate in macOS 13.3 and later has been added to R 4.4.0.

Threading in Accelerate is controlled by ‘Grand Central Dispatch’92 and is said not to need user control. Test `nls.R` in package stats has often failed with the Accelerate BLAS on Intel macOS.

Looking at the top of `/Library/Frameworks/R.framework/Resources/etc/Makeconf` will show the compilers and configuration options used for the CRAN binary package for R: at the time of writing the non-default options

    --enable-memory-profiling --enable-R-framework
    --x-libraries=/opt/X11/lib --x-includes=/opt/X11/include

were used. (`--enable-R-framework` implies `--enable-R-shlib`.)

The main TeX implementation used by the developers is MacTeX93 (https://www.tug.org/mactex/): the full installation is about 8.5GB, but a much smaller version (‘Basic TeX’) is available at https://www.tug.org/mactex/morepackages.html to which you will need to add some packages to build R, e.g. for the 2022 version we needed to add94 helvetic, inconsolata and texinfo which brought this to about 310MB.95 ‘`TeX Live Utility`’ (available via the MacTeX front page) provides a graphical means to manage TeX packages. These contain executables which run natively on both ‘`x86_64`’ and ‘`arm64`’.

Checking packages thoroughly requires ghostscript (part of the full MacTeX distribution or separately from https://www.tug.org/mactex/morepackages.html) and `qpdf` (from https://mac.r-project.org/bin//, a version of which is in the `bin` directory of a binary installation of R, usually `/Library/Frameworks/R.framework/Resources/bin/qpdf`).

`R CMD check --as-cran` makes use of ‘HTML Tidy’. macOS has a version in `/usr/bin/tidy` dating from 2006 which is far too old and is skipped. Up-to-date versions can be installed from http://binaries.html-tidy.org/.

One macOS quirk is that the default path has `/usr/local/bin` after `/usr/bin`, contrary to common practice on Unix-alikes. This means that if you install tools from the sources they will by default be installed under `/usr/local` and not supersede the system versions.

Parallel installation of packages will make use of the utility `timeout` if available. A dual-architecture build can be downloaded from https://www.stats.ox.ac.uk/pub/bdr/timeout: make it executable (`chmod 755 timeout`) and put it somewhere on your path.

#### C.3.6 Tcl/Tk headers and libraries

If you plan to use the `tcltk` package for R, you will need to install a distribution of Tcl/Tk. There are two alternatives. If you use R.APP you will want to use X11-based Tcl/Tk (as used on other Unix-alikes), which is installed under `$LOCAL/lib` as part of the CRAN binary for R.96 This may need `configure` options

    --with-tcltk=$LOCAL/lib

or

    --with-tcl-config=$LOCAL/lib/tclConfig.sh
    --with-tk-config=$LOCAL/lib/tkConfig.sh

Note that this requires a matching XQuartz installation.

There is also a native (‘Aqua’) version of Tcl/Tk which produces widgets in the native macOS style: this will not work with R.APP because of conflicts over the macOS menu, but for those only using command-line R this provides a much more intuitive interface to Tk for experienced Mac users. Earlier versions of macOS came with an Aqua Tcl/Tk distribution but these were often not at all recent versions of Tcl/Tk. It is better to install Tcl/Tk 8.6.x from the sources97 or a binary distribution from https://www.activestate.com/products/tcl/. For the latter, configure R with

    --with-tcl-config=/Library/Frameworks/Tcl.framework/tclConfig.sh
    --with-tk-config=/Library/Frameworks/Tk.framework/tkConfig.sh

If you need to find out which distribution of Tk is in use at run time, use

    library(tcltk)
    tclvalue(.Tcl("tk windowingsystem"))  # "x11" or "aqua"

Note that some Tcl/Tk extensions only support the X11 interface: this includes `Tktable` and the CRAN package tkrplot.

#### C.3.7 Java

macOS does not comes with an installed Java runtime (JRE) and a macOS upgrade may remove one if already installed: it is intended to be installed at first use. Check if a JRE is installed by running `java -version` in a `Terminal` window: if Java is not installed98 this should prompt you to install it.99 Builds of OpenJDK may also be available, e.g. from Adoptium, Azul or https://jdk.java.net/. We recommend you install a version with long-term support, e.g. 11 or 17 or (expected in 2023-09) 21 but not 12–16 nor 18–20 which have/had a 6-month lifetime. (Note that these sources may use unusual designations for Intel macOS builds such as `x86 64-bit` and `x64`.)

Binary distributions of R are built against a specific version (e.g. 11.0.6 or 17.0.1) of Java so `sudo R CMD javareconf` will likely be needed to be run before using Java-using packages.

To see what compatible versions of Java are currently installed, run the appropriate one of

    /usr/libexec/java_home -V -a x86_64
    /usr/libexec/java_home -V -a arm64

If needed, set the environment variable `JAVA_HOME` to choose between these, both when R is built from the sources and when `R CMD javareconf` is run.

Configuring and building R both looks for a JRE and for support for compiling JNI programs (used to install packages rJava and JavaGD); the latter requires a JDK (Java SDK). Most distributions of Java 9 or later are of a full JDK.

The build process tries to fathom out what JRE/JDK to use, but it may need some help, e.g. by setting environment variable `JAVA_HOME`. To select a build from Adoptium set e.g.

    JAVA_HOME=/Library/Java/JavaVirtualMachines/termurin-17.jdk/Contents/Home

in `config.site`. For Java 17 from https://jdk.java.net/ (which is no longer available), use

    JAVA_HOME=/path/to/jdk-17.jdk/Contents/Home

For an ‘`arm64`’ build, the earliest Java version which is officially supported is 17. The currently simplest way to install Java is from Adoptium (who call the architecture ‘`aarch64`’): this installs into an Apple-standard location and so works with `/usr/bin/java`. Other builds are available from https://www.azul.com/downloads/zulu-community/?os=macos&architecture=arm-64-bit&package=jdk and from OpenJDK at https://jdk.java.net/, for which `JAVA_HOME` may need to be set both when configuring R and at runtime.

To use Java (specifically, binary package rJava) with a CRAN (‘`x86_64`’) binary distribution of R on ‘`arm64`’ macOS, install an Intel build of a Java JRE from one of the sites linked above, then run `sudo R CMD javareconf`.

Note that it is necessary to set the environment variable `NOAWT` to `1` to install many of the Java-using packages.

#### C.3.8 Frameworks

The CRAN build of R is installed as a framework, which is selected by the option

    ./configure --enable-R-framework

(This is intended to be used with an Apple toolchain: others may not support frameworks correctly but those from LLVM do.)

It is only needed if you want to build R for use with the R.APP console, and implies `--enable-R-shlib` to build R as a dynamic library. This option configures 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 `--prefix`) or at install time via

    make prefix=/where/you/want/R.framework/to/go install

Note that installation as a framework is non-standard (especially to a non-standard location) and Unix utilities may not support it (e.g. the `pkg-config` file `libR.pc` will be put somewhere unknown to `pkg-config`).

#### C.3.9 Building R.app

Building the R.APP GUI console is a separate project, using Xcode. Before compiling R.APP make sure the current version of R is installed in `/Library/Frameworks/R.framework` and is working at the command-line (this can be a binary install).

The current sources can be checked out by

    svn co https://svn.r-project.org/R-packages/trunk/Mac-GUI

and built by loading the `R.xcodeproj` project (select the `R` target and a suitable configuration), or from the command-line by e.g.

    xcodebuild -target R -configuration Release

See also the `INSTALL` file in the checkout or directly at https://svn.r-project.org/R-packages/trunk/Mac-GUI/INSTALL.

R.APP does not need to be installed in any specific way. Building R.APP results in the R.APP bundle which appears as one R icon. This application bundle can be run anywhere and it is customary to place it in the `/Applications` folder.

#### C.3.10 Building binary packages

CRAN macOS binary packages are distributed as tarballs with suffix `.tgz` to distinguish them from source tarballs. One can `tar` an existing installed package, or use `R CMD INSTALL --build`.

However, there are some important details.

- Current CRAN macOS distributions are targeted at Big Sur so it is wise to ensure that the compilers generate code that will run on Big Sur or later. With the recommended compilers we can use

      CC="clang -mmacosx-version-min=11.0"
      CXX="clang++ -mmacosx-version-min=11.0"
      FC="/opt//gfortran/bin/gfortran -mmacosx-version-min=11.0"

  or set the environment variable

      export MACOSX_DEPLOYMENT_TARGET=11.0

- Using the flag `-Werror=partial-availability` can help trigger compilation errors on functionality not in Big Sur.
- Check that any compiled code is not dynamically linked to libraries only on your machine, for example by using `otool -L` or `objdump -macho -dylibs-used`. This can include C++ and Fortran run-time libraries under `/opt/R/x86_64/lib` or `/opt/R/arm64/lib`: one can use `install_name_tool` to point these at system versions or those shipped with R, for example

      install_name_tool -change /usr/local/llvm/lib/libc++.1.dylib \
      /usr/lib/libc++.1.dylib \
      pkg.so

      install_name_tool -change
      /opt/gfortran/lib/gcc/aarch64-apple-darwin20.0/12.2.0/libgfortran.5.dylib \
      /Library/Frameworks/R.framework/Resources/lib/libgfortran.5.dylib \
      pkg.so

      install_name_tool -change
      /opt/gfortran/lib/gcc/aarch64-apple-darwin20.0/12.2.0/libquadmath.0.dylib \
      /Library/Frameworks/R.framework/Resources/lib/libquadmath.0.dylib \
      pkg.so

  (where the details depend on the compilers and CRAN macOS R release).

- For C++ code there is the possibility that calls will be generated to entry points not in the system `/usr/lib/libc++.1.dylib`. The previous step allows this to be tested against the system library on the build OS, but not against earlier ones. It may be possible to circumvent that by static linking to `libc++.a` and `libc++abi.a` by something like

      SHLIB_CXXLD = /usr/local/llvm/bin/clang
      PKG_LIBS = /usr/local/llvm/lib/libc++.a /usr/local/llvm/lib/libc++abi.a

  in `src/Makevars`. It would also be possible to static link the Fortran runtime libraries `libgfortran.a` and `libquadmath.a` should the Fortran compiler have later versions (but `gfortran` 8–13 all have version `5`).

The CRAN binary packages are built with the Apple compiler on the oldest supported version of macOS, which avoids the first two and any issues with C++ libraries.

#### C.3.11 Building for Intel on ‘`arm64`’

Should one want to build R for Intel on an ‘`arm64`’ Big Sur Mac, add the target for the C and C++ compilers:

    CC="clang -arch x86_64
    OBJC=$CC
    CXX="clang++ -arch x86_64"
    FC="/opt//gfortran/bin/gfortran -arch x86_64 -mtune=native -mmacosx-version-min=11"

and install the Fortran compiler and external software described above for Intel builds (and have `/opt/R/x86_64/bin` before `/opt/R/arm64/bin` in your path).

To set the correct architecture (which will be auto-detected as `aarch64`), use something like

    /path/to/configure --build=x86_64-apple-darwin20

#### C.3.12 Installer

The scripts for the CRAN packaging of R can be found under https://svn.r-project.org/R-dev-web/trunk/QA/Simon/R4/: start with the `README` file in that directory.

### C.4 FreeBSD

There have been few recent reports on FreeBSD: there is a ‘port’ at https://svnweb.freebsd.org/ports/head/math/R, currently last updated for R 4.0.4. Recent versions of FreeBSD use Clang and the `libc++` C++ headers and runtime, but the ‘port’ has been configured to use GCC.

Use of ICU for collation and the `configure` option `--with-internal-tzcode` are desirable workarounds.

### C.5 OpenBSD

Ingo Feinerer installed R version 3.2.2 on OpenBSD 5.8 arch ‘`amd64`’ (their name for ‘`x86_64`’). Details of the build (and patches applied) are at https://cvsweb.openbsd.org/cgi-bin/cvsweb/ports/math/R/, currently updated for R 4.2.1.

### C.6 Cygwin

The 32-bit version never worked well enough to pass R’s `make check`, and residual support from earlier experiments was removed in R 3.3.0.

The 64-bit version was never supported.

### C.7 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 required that computation be done with a `-ieee_with_inexact` flag etc. With Intel compilers on 32-bit and 64-bit Intel machines, one has to explicitly disable flush-to-zero and denormals-are-zero modes. Some ARM processors including A12Z and M1 (Apple Silicon) by default use runfast mode, which includes flush-to-zero and default-nan and hence has to be disabled. With default-nan mode, the NaN payload used for representation of numeric NA values is lost even on simple operations with finite values. 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 Oracle compilers has caused R’s `NaN` to be set incorrectly, and `gcc`’s `-ffast-math` and `clang`’s `-Ofast` have given incorrect results.

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 or with additional flags. Set the configure variable `SAFE_FFLAGS` to the flags to be used for this file.

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 ...

One thing you might want to add for a new platform is the mapping of C/C++/Fortran calls to entry point names used for `R CMD check`. See https://svn.r-project.org/R-dev-web/trunk/sotools.txt for how to do so.

## Function and variable index

Jump to: | C I M R U

| 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

Jump to: | C I M R U

## Concept index

Jump to: | B C F I L M O P R S U V

| Index Entry |  | Section
B |  |
| BLAS library: |  | Linear algebra
| BLAS library: |  | Other libraries
C |  |
| Cairo: |  | Installing R under macOS
| Cairo: |  | Useful libraries and programs
| Cairo: |  | X11 issues
| Cairo: |  | Cairo graphics
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: |  | Other libraries
| 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 |  |
| macOS: |  | Installing R under Unix-alikes
| macOS: |  | Installing R under macOS
| macOS: |  | macOS
| Manuals: |  | Making the manuals
| Manuals, installing: |  | Installation
O |  |
| Obtaining R: |  | Obtaining R
| OpenBSD: |  | OpenBSD
P |  |
| Packages: |  | Add-on packages
| Packages, default: |  | Default packages
| Packages, installing: |  | Installing packages
| Packages, removing: |  | Removing packages
| Packages, updating: |  | Updating packages
| Pango: |  | Useful libraries and programs
| Pango: |  | Cairo graphics
R |  |
| Repositories: |  | Setting up a package repository
S |  |
| Site libraries: |  | Managing libraries
| 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

Jump to: | B C F I L M O P R S U V

## Environment variable index

Jump to: | B C D J L P R T

| Index Entry |  | Section
B |  |
| `BLAS_LIBS`: |  | BLAS
C |  |
| `CONFIG_SITE`: |  | Configuration variables
D |  |
| `DESTDIR`: |  | Installation
| `DESTDIR`: |  | Unix-alike standalone
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`: |  | Using Fortran
| `LD_LIBRARY_PATH`: |  | Compile and load flags
P |  |
| `PAPERSIZE`: |  | Setting paper size
| `PATH`: |  | Essential programs and libraries
| `PATH`: |  | Using Fortran
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_SCRIPT_DEFAULT_PACKAGES`: |  | Default packages
| `R_USER`: |  | Running R
T |  |
| `TAR`: |  | Essential programs and libraries
| `TAR_OPTIONS`: |  | Getting and unpacking the sources
| `TEMP`: |  | Running R
| `TMP`: |  | Running R
| `TMPDIR`: |  | Simple compilation
| `TMPDIR`: |  | Running R
| `TMPDIR`: |  | Running R
| `TMPDIR`: |  | Installing packages

Jump to: | B C D J L P R T

#### Footnotes

##### (1)

e.g. GNU `tar` version 1.15 or later, or that from the ‘`libarchive`’ (as used on macOS) or ‘Heirloom Toolchest’ distributions.

##### (2)

for some Subversion clients ‘`http:`’ may appear to work, but requires continual redirection.

##### (3)

aka ‘Apple Silicon’, known to some as ‘`arm64-apple-darwin`’.

##### (4)

Spaces were discouraged but allowed prior to R 4.3.0.

##### (5)

which use `lib` rather than `lib64` for their primary 64-bit library directories: attempts are made to detect such systems.

##### (6)

not by the version supplied by macOS.

##### (7)

Instructions on how to install the latest version are at https://www.ctan.org/tex-archive/fonts/inconsolata/.

##### (8)

on a Unix-alike, ‘`inconsolata`’ is omitted if not found by `configure`.

##### (9)

This will be needed if more than one sub-architecture is to be installed.

##### (10)

with possible values ‘`i386`’, ‘`x64`’, ‘`32`’ and ‘`64`’.

##### (11)

mainly on RedHat and Fedora, whose layout is described here.

##### (12)

How to prepare such a directory is described in file `src/extra/tzone/Notes` in the R sources.

##### (13)

But on Windows problems have been seen with case-changing functions on accented Latin-1 characters.

##### (14)

for example, `-fopenmp`, `-fiopenmp`, `-xopenmp` or `-qopenmp`. This includes for `clang` and the Intel and Oracle compilers.

##### (15)

This does not necessarily disable use of OpenMP – the `configure` code allows for platforms where OpenMP is used without a flag. For the `flang` compiler in late 2017, the Fortran runtime always used OpenMP.

##### (16)

Then recommended packages installed as part of the R installation do use LTO, but not packages installed later.

##### (17)

A complete CRAN installation reduced from 50 to 35GB.

##### (18)

although there is the possibility to exclude Fortran but that misses some of the benefits.

##### (19)

not `NM` as we found `make` overriding that.

##### (20)

probably also 8.4 and later.

##### (21)

There are reports of segfaults when ‘`MiKTeX`’ installs additional packages when making `NEWS.pdf`: re-running `make` seems to solve this.

##### (22)

You may be asked to install Rosetta at first use – https://support.apple.com/en-us/HT211861 – which may need administrator privileges.

##### (23)

At the time of writing, version 2.8.5 or later.

##### (24)

The installer puts links to `R` and `Rscript` in `/usr/local/bin`. If these are missing or that is not on your path, you can run directly the copies in `/Library/Frameworks/R.framework/Resources/bin` or link those yourself to somewhere on your path.

##### (25)

At the time of writing: use `pkgutil --pkgs | grep -i org.r-project` to check.

##### (26)

More precisely, of the Apple package of the same name: this means that Intel and ARM versions can be installed together.

##### (27)

Including GCC 9 on Linux.

##### (28)

On Windows a path containing spaces will be replaced by the ‘short path’ version if that does not contain spaces.

##### (29)

unless they were excluded in the build.

##### (30)

its binding is locked once the startup files have been read, so users cannot easily change it. See `?.libPaths` for how to make use of the new value.

##### (31)

If a proxy needs to be set, see `?download.file`.

##### (32)

for a small number of CRAN packages where this is known to be safe and is needed by the autobuilder this is the default. Look at the source of `tools:::.install_packages` for the list. It can also be specified in the package’s `DESCRIPTION` file.

##### (33)

Note that capitalization and versioning may differ from the Open Source project.

##### (34)

From Big Sur those libraries are not publicly visible: rather the system compilers link to ‘text-based definition’ (`.tbd`) files.

##### (35)

using a path containing spaces is likely to cause problems

##### (36)

They need to have been created using `-headerpad_max_install_names`, which is the default for an R package.

##### (37)

‘X/Open Portability Guide’, which has had several versions.

##### (38)

On some systems setting `LC_ALL` or `LC_MESSAGES` to ‘`C`’ disables `LANGUAGE`.

##### (39)

If you try changing from French to Russian except in a UTF-8 locale, you may find messages change to English.

##### (40)

the language written in England: some people living in the USA appropriate this name for their language.

##### (41)

with Americanisms.

##### (42)

also known as IEEE 754

##### (43)

at least when storing quantities: the on-FPU precision is allowed to vary

##### (44)

e.g. Bessel, beta and gamma functions

##### (45)

including copying `MkRules.dist` to `MkRule.local` and selecting the architecture.

##### (46)

also known as IEEE 754

##### (47)

Note that C11 compilers need not be C99-compliant: R requires support for `double complex` and variable-length arrays which are optional in C11 but are mandatory in C99. C17 (also known as C18 as it was published in 2018) is a ‘bugfix release’ of C11, clarifying the standard. However, all known recent compilers in C11 or C17 mode are C99-compliant, and most default to C17.

##### (48)

Examples are `-std=gnu99`, `-std=c99` and `-c99`.

##### (49)

However, it is possible to break the default behaviour of `glibc` by re-specifying the `gconv` modules to be loaded.

##### (50)

specifically, the C99 functionality of headers `wchar.h` and `wctype.h`, types `wctans_t` and `mbstate_t` and functions `mbrtowc`, `mbstowcs`, `wcrtomb`, `wcscoll`, `wcstombs`, `wctrans`, `wctype`, and `iswctype`.

##### (51)

including `expm1`, `hypot`, `log1p`, `nearbyint` and `va_copy`.

##### (52)

including `opendir`, `readdir`, `closedir`, `popen`, `stat`, `glob`, `access`, `getcwd` and `chdir` system calls, `select` on a Unix-alike, and either `putenv` or `setenv`.

##### (53)

such as `realpath`, `symlink`.

##### (54)

most often distributed as part of `xz`: possible names in Linux distributions include `xz-devel`/`xz-libs` and `liblzma-dev`.

##### (55)

for example to specify static linking with a build which has both shared and static libraries.

##### (56)

Such as GNU `tar` 1.15 or later, `bsdtar` (from https://github.com/libarchive/libarchive/, used as `tar` by FreeBSD and macOS 10.6 and later) or `tar` from the Heirloom Toolchest (https://heirloom.sourceforge.net/tools.html), although the latter does not support `xz` compression.

##### (57)

`texi2dvi` is normally a shell script. Some of the issues which have been observed with broken versions of `texi2dvi` can be circumvented by setting the environment variable `R_TEXI2DVICMD` to the value `emulation`.

##### (58)

If necessary the path to `pkg-config` can be specified by setting `PKG_CONFIG` in `config.site`, on the `configure` command line or in the environment. There is a compatible re-implementation of `pkg-config` called `pkgconf` which can be used in the unlikely event that is installed but not linked to `pkg-config`.

##### (59)

also known as `ttf-mscorefonts-installer` in the Debian/Ubuntu world: see also https://en.wikipedia.org/wiki/Core_fonts_for_the_Web.

##### (60)

`ttf-liberation` in Debian/Ubuntu.

##### (61)

Including that used by Fedora.

##### (62)

R uses `rpc/xdr.h` but that includes `netconfig.h` from the top `tirpc` directory.

##### (63)

This is true even for the ‘Aqua’ version of Tk on macOS, but distributions of that include a copy of the X11 files needed.

##### (64)

The search order is currently OpenBLAS, BLIS, ATLAS, platform-specific choices (see below) and finally a generic `libblas`.

##### (65)

Using the Oracle Developer Studio `cc` and `f95` compilers

##### (66)

The only way to see exactly which CPUs the distributed libraries have been tuned for is to read the `atlas.spec` file.

##### (67)

https://math-atlas.sourceforge.net/atlas_install/

##### (68)

https://math-atlas.sourceforge.net/faq.html#tnum

##### (69)

(and more, e.g. for 64-bit ints and static versions).

##### (70)

Nowadays known as ‘Intel oneAPI Math Kernel Library’ or even ‘oneMKL’.

##### (71)

The issue for macOS has been the use of double-complex routines.

##### (72)

ATLAS, OpenBLAS and Accelerate.

##### (73)

We have measured 15–20% on ‘`i686`’ Linux and around 10% on ‘`x86_64`’ Linux.

##### (74)

We believe that versions 3.4.0 to 3.19.0 are compatible.

##### (75)

at the time of revision of this para in late 2021, autoconf-2.71 and automake-1.16.5. Subsequently autoconf-2.72 has been tested.

##### (76)

The links there have proved difficult to access, in which case grab the copy made available at https://developer.r-project.org/noweb-2.11b.tgz.

##### (77)

Most `clang`-based compilers give `4`, but not those distributed by FreeBSD. Intel’s `icx` reported `12` in 2023.

##### (78)

for example, `X11 font at size 14 could not be loaded`.

##### (79)

For example, `glibc`: other C libraries such as `musl` (as used by Alpine Linux) have been used but are not routinely tested.

##### (80)

Likely all since 2005, including Pentium 4 and all ‘`x86_64`’ CPUs with 32-bit compilers.

##### (81)

This also needs the OpenMP runtime which has sometimes been distributed separately.

##### (82)

as the compiler has been known on Windows.

##### (83)

it will if R has been installed from CRAN since R 4.3.0.

##### (84)

If compiling it from source on ‘`arm64`’, `pcre2` (at least up to version 10.39) needs to be built without JIT support (the default) as the R build segfaults if that is enabled, so do run `make check` on your build.

##### (85)

For licence reasons this is version 5.2 of `readline`: for those who want a more recent version it is straightforward to compile it from its sources.

##### (86)

`ls -l `xcrun -show-sdk-path`` in a terminal will show you which SDK is selected.

##### (87)

See https://developer.apple.com/documentation/xcode/notarizing_macos_software_before_distribution.

##### (88)

with `gcc` 10.2.

##### (89)

https://developer.apple.com/documentation/accelerate.

##### (90)

It has been reported that for some non-Apple toolchains `CPPFLAGS` needed to contain `-D__ACCELERATE__`: not needed for `clang` from LLVM.

##### (91)

https://cran.r-project.org/bin/macosx/RMacOSX-FAQ.html#Which-BLAS-is-used-and-how-can-it-be-changed_003f

##### (92)

E.g., https://en.wikipedia.org/wiki/Grand_Central_Dispatch .

##### (93)

An essentially equivalent TeX installation can be obtained by the Unix TeX Live installation scripts.

##### (94)

E.g. via `tlmgr install helvetic inconsolata texinfo` .

##### (95)

Adding all the packages needed to check CRAN increased this to about 600MB.

##### (96)

Just that component can be selected from the installer for R: at the ‘Installation Type’ screen select ‘Customise’ and then just the ‘Tcl/Tk 8.6.11’ component.

##### (97)

Configure Tk with `--enable-aqua`.

##### (98)

In the unlikely event that the version reported does not start with `1.8.0`, `11` or higher you need to update your Java.

##### (99)

Not at the time of writing for ‘`arm64`’.