R packages

What’s on this page?

• How to add packages to base R installation.
  • How to select a CRAN mirror site.
  • Steps for package installation from selected CRAN mirror site.
  • How to load and unload a package.
• How to update installed packages following an upgrade of R.
• List of R packages used in the Mike’s Biostatistics Book.

The instructions on this page chiefly apply to an installation of R on a local computer, Linux, macOS, or winPC. Running R in the cloud (eg, Google CoLab) also requires installing and loading packages, but many of the other instructions on this page do not apply. Look for the CoLab, skip this step: statement; instructions lacking this disclaimer should apply to CoLab. After a skip this step: statement, I’ll start the new section with Applies to all.

Add packages to base R installation

CoLab, skip this step: it is not necessary to set a mirror site for Google CoLab.

Installing R packages is straightforward, assuming the package is part of CRAN. Select a CRAN mirror site, eg, 0-Cloud, RStudio’s mirror site.

chooseCRANmirror()

To find out what CRAN mirror was set for the current session use

findCRANmirror()

A list of mirror sites is stored on your computer once R is installed, see CRAN_mirrors.csv in the doc folder, eg, ~/R-4.3.1/doc.

Applies to all. Once the CRAN mirror is selected, and assuming you have the name of the package, eg, package.name, then

install.packages("package.name")

will work.

Useful additional command options include

install.packages("package.name", dependencies=TRUE)

which will also download and install any additional packages required. And

install.packages("package.name", quiet=TRUE)

which cuts down on the amount of screen output during installation.

If you receive the warning message

Warning: package 'package.name' is not available (for R version 4.3.2)

While it is possible the package has not yet become available, first double-check for typos.

Another warning message may be that a binary version is available, but a more recent source version is available, prompted by the question,

Do you want to install from sources the package which needs compilation?

In most cases, no is the answer. R will install a previous binary version. In order to install from source, RTools must be installed.

RTools contains software tools needed to build some R packages on WinPC.

Start, stop, or remove package

Applies to all. library("package name") is used to start a package. If a package is to be called in a function, then use require("package name"). If the called package is not installed, library() will exit with an error message whereas the function will continue to run if require() is used.

To unload a package without stopping current R session, try detach("package name") or unloadNamespace("package name"). The command remove.packages("package name") will uninstall a package from R.

Update R packages after installing new R version

CoLab, skip this step: After updating to new version of R you’ll need to download and update the user installed packages again. If you are running RStudio, see instructions here. For Win11 users you can download and run a package called installr, for macOS users download and install updateR, which will assist you to update R packages.

I prefer to run a script I modified from R-Bloggers.com. This script works on any operating system, but updates only CRAN packages (eg, not devtools github or Bioconductor packages). For github, try . dtupdate. For Bioconductor, see BiocManager::install() ).

Before installing the new version of base R, start up your current R installation and set your working directory, setwd(). Enter the following script to gather and save all installed R packages. Select CRAN mirror when prompted.

tmp <- installed.packages()
installedpkgs <- as.vector(tmp[is.na(tmp[,"Priority"]), 1])
save(installedpkgs, file="installed_old.rda")

Shutdown R, then install and start the new version of R (see Install R for help).

In the new version of R, set your working directory as above. Enter the following script

load(file="installed_old.rda")
tmp <- installed.packages()
installedpkgs.new <- as.vector(tmp[is.na(tmp[,"Priority"]), 1])
missing <- setdiff(installedpkgs, installedpkgs.new)
install.packages(missing)
update.packages(ask=FALSE)

Should be good to go. You can remove old R version installation.

R packages used in Mike’s Biostatistics Book

list updated 12 August 2024