Installing R packages locally: Difference between revisions

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== Installing to a local library search location ==
== Installing to a local library search location ==


Installation is dead easy. Start up R and tell R to fetch your package from CRAN, compile whatever needs compiling and set everything else up.
Start up R:
 
Beware - each package will only work for the platform (i.e. Linux or Solaris) where you installed it. If you want a package on both Linux and Solaris, you'll need to install it in different directories for each system type.


<source lang='bash'>
<source lang='bash'>
   R                    # Invoke R
   R                    # Invoke R
</source>
</source>
Then, from the R environment, install the packages you require while pointing at the root R-package directory of choice:
Then, from the R environment, install the packages you require while pointing at the root R-package directory of choice. This example will install from CRAN.
<source lang='rsplus'>
<source lang='rsplus'>
install.packages("name-of-your-package",lib="~/R/library")
install.packages("name-of-your-package",lib="~/R/library")

Revision as of 21:27, 26 November 2013


Specifying a local library search location

Specify a local library search location.

You can use several library trees of add-on packages. The easiest way to tell R to use these via a 'dotfile' by creating the following file '$HOME/.Renviron' (watch the quotes and ~ character): <source lang='bash'>

 R_LIBS_USER="~/R/library"

</source> This specifies a keyword (R_LIBS_USER) which points to a colon-separated list of directories at which R library trees are rooted. You do not have to specify the default tree for R packages.

If necessary, create a place for your R libraries <source lang='bash'>

 mkdir ~/R ~/R/library         # Only need do this once

</source> Set your R library path <source lang='bash'>

 echo 'R_LIBS_USER="~/R/library"' >  $HOME/.Renviron

</source>

Installing to a local library search location

Start up R:

<source lang='bash'>

 R                     # Invoke R

</source> Then, from the R environment, install the packages you require while pointing at the root R-package directory of choice. This example will install from CRAN. <source lang='rsplus'> install.packages("name-of-your-package",lib="~/R/library") </source>

See also

External links

source for material for this aricle