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1. Software Installation Instructions

Sara Khan edited this page Jul 1, 2019 · 3 revisions

If you will be participating in one of our training workshops (or teaching yourself using our online materials), you'll need to download the software as described on this page. We recommend working with the most recent versions. So even if you already have installed some of the software required, consider updating it if newer versions are available.

Downloading R and Rstudio

All of our software is built on the R computing platform. R a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS.

You can download the version of R appropriate for your system from the Comprehensive R Archive Network (CRAN) site:

CRAN R download

We teach our workshops using Rstudio, an interface for R that provides simple GUI access to many commonly used R utilities, as well as integrated support for code repositories and markdown-based document production. Rstudio also offers a free version. Rstudio is recommended, but not required, to access R and the statnet software.

You can download the version of Rstudio appropriate for your system from the Rstudio website:

Rstudio Desktop download

Downloading statnet packages

Technically statnet is a suite of R packages that perform a wide range of data management, visualization, descriptive and statistical network analysis tasks. The number of packages in the suite is continuing to grow, providing access to new methodology as we develop it.

All statnet packages are downloaded/installed through the R interface, so you'll need to download and launch R first.

There are two basic approaches to installing the statnet software:

  1. Install the statnet R meta-package: This provides a simple one-step approach to installing the core packages in the statnet suite, and their dependencies. It is a convenient approach, especially for beginners.
  2. Install the individual packages directly, which will automatically install their dependencies. This is useful if you know you only need one package, and necessary for the packages not loaded by statnet.

You should pick the approach best suited to your needs.

Installing the statnet metapackage

From the R command line:

> install.packages("statnet")

This will download from CRAN and install in your RLibrary the following packages: network, sna, ergm, networkdynamic, tsna, tergm, ergm.count and statnet.common. If you want to find out where the RLibrary directory is on your system, type:

> .libPaths()

You will then need to:

> library(statnet)

to use the packages in R.

Installing individual packages from the statnet suite

We'll use the package ergm as an example here. From the R command line:

> install.packages("ergm")

This will download from CRAN and install in your RLibrary the ergm package, as well as the other packages that ergm depends on: network and statnet.common.

You will then need to:

> library(ergm)

to use the packages in R.

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