The SIENA methods are available in
which is a package of the statistical system R.
RSiena can be executed on all platforms
for which R is available: Windows, Mac, Unix/Linux.
R can be downloaded from the Comprehensive R Archive Network
https://cran.r-project.org, and RSiena can be
loaded as one of the packages in R.
In addition,there is a package multiSiena which includes
the function sienaBayes and which can be downloaded from the
Siena downloads page.
RSiena can be installed in the usual way from CRAN,
but the most recent version of RSiena can be downloaded from
It is expected that at some moment multiSiena will be integrated
For downloading RSiena and multiSiena, see the
Siena downloads page.
For differences between the CRAN and GitHub versions of RSiena, see the
Siena news page.
Note that the GitHub version is updated more frequently than the CRAN version,
as explained there.
For requests of new effects or other new features, bug reports, etc.
open an issue at github.
The original development of RSiena, building on the earlier
Siena (stand-alone and part of the Stocnet suite) was
part of the project Adolescent Peer Social Network Dynamics
and Problem Behavior, funded by NIH (Grant Number 1R01HD052887-01A2),
Principal Investigator John M. Light (Oregon Research Institute).
RSiena was originally programmed by
Ruth Ripley and Krists Boitmanis, in collaboration with Tom Snijders.
Several others have been contributing since then: Josh Lospinoso, Charlotte Greenan, Christian Steglich,
Johan Koskinen, Felix Schönenberger, Mark Ortmann, Natalie Indlekofer, and Nynke Niezink.
The maintainer is
We are continuing with the extension of the package.
The fact that R is open source implies that the source is available
(most easily from GitHub, see below) and the project is open
to contributions by other researchers
who know how to program in R and/or C/C++.
RSiena replaces the older Windows-based SIENA version 3,
which still is available from the downloads page,
but no longer maintained.
RSiena can be operated in several ways.
The best (most complete) functionality is obtained by
executing RSiena entirely within R, using the R functions supplied
by this package.
An alternative option is to access RSiena from
a short guide is available
at the visone website.
The installation and operation of RSiena are explained
in the users' manual.
It includes information on how to install RSiena,
and help on getting started with operating RSiena in R.
In addition, it gives extensive descriptions of the methods available
This complements the help pages of the functions that can be consulted within R.
Example scripts are at the
RSiena scripts page,
and a lot of introductory and advanced material about the methodology is at the
There is news, with information about bugs if any important errors are currently known,
at the news page.
RSiena and its manual are being updated rather frequently at
Downloads / links
- For downloading RSiena and multiSiena,
go to the Siena downloads page.
- You can download the current RSiena users' manual.
- Some websites and resources that can be very helpful for the beginning R user:
Self-Learning Resources for R from Princeton.
- General information
about R from UCLA.
Impatient R, previously
Some Hints for the R Beginner, by Patrick Burns with
the memorable quote
"I asked R users what their biggest stumbling blocks were in learning R.
A common answer that I was quite surprised by was that the biggest
stumbling block was thinking that R was hard".
Introduction to Data Exploration and Analysis with R by Michael Mahoney.
This book is designed as a crash course in coding with R and data analysis,
built for people trying to teach themselves.
- Quick R website
(intended especially for experienced users of other statistical software).
tutorials for learning R by Tal Galili.
- The official R intro
(always for the current version of R).
- Further general help on R:
Course on R and R programming by Ruth Ripley.
- The "Documentation" links on
- R reference card.
an integrated development environment
(IDE) for R, available for all major platforms (like g Windows, Mac OS X, and Linux).
This is an alternative to the R gui available for Windows.
- Another alternative, or rather a convenient
NpptoR, which easily passes on code from the
(which has nice syntax highlighting) to R.
- An introductory R script
for starting with R, using
IMF data collected by David de Jong.
- An introductory R script
to learn R for Social Networks applications, using the
Lazega lawyers data ,
which can also be directly downloaded from
this directory with data files.
Introduction to Social Network Analysis in R
by Michal Bojanowski (ICM, University of Warsaw).
a central hub of content collected from bloggers who write about R (in English).
- The RSiena information
at CRAN (the Comprehensive R Archive Network).