Carter's Archive of S Routines for the R Statistical Computing Environment

Most of which involve social network analysis, though a wee bit 'o other stuff is available as well....


SNA Package Logo
Link to Sociology Site
Link to IMBS Site
Link to CRAN Site


Introduction and Caveats

This page serves, as one might expect, to allow other researchers to access some of the data analysis tools I've developed in the S language. The implementation of S used here is that of the R Statistical Computing Environment, rather than the common alternative of S-PLUS; the intrepid could doubtless port these routines from one flavor of the language to the other, however.

Caveats: This software is provided on an unsupported, as-is basis, under the terms of the GNU Public License. It is not guaranteed to be bug-free, let alone efficient; use it at your own risk. While the author is always happy to hear about bugs (and is sometimes happy to hear about suggestions and/or demands), he makes no promises whatsoever about making changes to the software, now or in the future. Amen.

Getting and Using R

The R statistical computing environment is distributed under the GNU Public License, and can be freely obtained either as source or as precompiled binaries for a wide range of platforms. The main R Project site has a great deal of information on the project and software, as well as pointers to other resources. For downloads, documentation, and the like, the Comprehensive R Archive Network (CRAN) site (or one of its mirrors) is the standard resource. Full details on installing and using the latest version of R can be found at these sites. Newcomers to S may also want to check out Venables and Ripley's Modern Applied Statistics with S-Plus, much of which is applicable to R, as well as the various manuals and tutorials listed on the CRAN web site.

The Statnet Project

Most of the material contained here is now part of the Statnet Project, a collaborative effort to develop Free Software tools for network analysis. Statnet incorporates packages such as sna and network, among many others, in a single interoperable toolkit. Find more information regarding Statnet at http://statnet.org.

Social Network Analysis Tools

The SNA Package, v2.2
This is a fully documented collection of R routines for social network analysis; utilities included range from hierarchical Bayesian modeling of informant accuracy to logistic network regression (with QAP and CUG tests). Quite a few low-level utilities for plotting and transforming networks are available as well, along with many of the usual centrality and distance measures. (Some sample plots are available.) To use under UNIX, execute the command `R CMD INSTALL /mypath/sna_2.2-0.tar.gz' from your command prompt. Under Windows, install the binary version (sna_2.2-0.zip) into your library directory (see your R documentation). After the installation completes, use `library(sna)' from within R to access the SNA Library. See the R documentation for details.

Files:

Current INDEX, ChangeLog, contributors list, and reference manual in Acrobat (PDF) format
sna_2.2-0.tar.gz (Source) and sna_2.2-0.zip (Binary) package files, and sna-manual.2.2.pdf (Manual) [Current]
sna_2.1-0.tar.gz (Source) and sna_2.1-0.zip (Binary) package files, and sna-manual.2.1.pdf (Manual)
sna_2.0-1.tar.gz (Source) and sna_2.0.zip (Binary) package files, and sna-manual.2.0.pdf (Manual)
sna_1.5.tar.gz (Source) and sna_1.5.zip (Binary) package files, and sna-manual.1.5.pdf (Manual)
sna_1.4.tar.gz (Source) and sna_1.4.zip (Binary) package files, and sna-manual.1.4.pdf (Manual)
sna_1.3.tar.gz (Source) and sna_1.3.zip (Binary) package files, and sna-manual.1.3.pdf (Manual)
sna_1.2.tar.gz (Source) and sna_1.2.zip (Binary) package files, and sna-manual.1.2.pdf (Manual)
sna_1.1.tar.gz (Source) and sna_1.1.zip (Binary) package files, and sna-manual.1.1.pdf (Manual)
sna_1.0-0.tar.gz (Source) and sna_1.0-0.zip (Binary) package files, and sna-manual.1.0-0.pdf (Manual)
sna_0.51-0.tar.gz (Source) and sna_0.51-0.zip (Binary) package files, and sna-manual.0.51-0.pdf (Manual)
sna_0.50-1.tar.gz (Source) and sna_0.50-1.zip (Binary) package files, and sna-manual.0.50-1.pdf (Manual)
sna_0.44-1.tar.gz (Source) and sna_0.44-1.zip (Binary) package files, and sna-manual.0.44-1.pdf (Manual)
sna_0.43.tar.gz (Source) and sna_0.43.zip (Binary) package files, and sna-manual.0.43.pdf (Manual)
sna_0.41.tar.gz (Source) and sna_0.41.zip (Binary) package files, and sna-manual.0.41.pdf (Manual)
sna_0.4.tar.gz (Source), sna_0.4.zip (Binary), and sna-manual.0.4.pdf (Manual)
sna_0.3.tar.gz, and manuals in PostScript and PDF formats
sna.0.2.R
sna.0.1.R

The network Package, v1.6
(Co-authored with Mark Handcock, Dave Hunter, and Martina Morris, with additional initial input from Dave Schruth and Daniel Westreich.)
The network package is a collection of tools for the creation and manipulation of network data objects. Network objects allow for simplified storage of complex vertex, edge, and network attributes, and scale more efficiently for large networks than adjacency matrices. The network package is compatible with sna, but the latter does not require it; several other packages, however, do require the network package in order to function. To use under UNIX, execute the command `R CMD INSTALL /mypath/network_1.6.tar.gz' from your command prompt. Under Windows, install the binary version (network_1.6.zip) into your library directory (see your R documentation). After the installation completes, use `library(network)' from within R to access the network Library. See the R documentation for details.

Note: network objects are not natively supported by sna versions prior to 1.0.
Files:

Current INDEX, ChangeLog and reference manual in Acrobat (PDF) format
network_1.6.tar.gz (Source) and network_1.6.zip (Binary) package files, and network-manual.1.6.pdf (Manual) [Current]
network_1.5.tar.gz (Source) and network_1.5.zip (Binary) package files, and network-manual.1.5.pdf (Manual)
network_1.4-1.tar.gz (Source) and network_1.4-1.zip (Binary) package files, and network-manual.1.4-1.pdf (Manual)
network_1.3.tar.gz (Source) and network_1.3.zip (Binary) package files, and network-manual.1.3.pdf (Manual)
network_1.2.tar.gz (Source) and network_1.2.zip (Binary) package files, and network-manual.1.2.pdf (Manual)
network_1.1-2.tar.gz (Source) and network_1.1-2.zip (Binary) package files, and network-manual.1.1-2.pdf (Manual)
network_1.1.tar.gz (Source) and network_1.1.zip (Binary) package files, and network-manual.1.1.pdf (Manual)
network_1.0-1.tar.gz (Source) and network_1.0-1.zip (Binary) package files, and network-manual.1.0-1.pdf (Manual)
network_0.5-4.tar.gz (Source) and network_0.5-4.zip (Binary) package files, and network-manual.0.5-4.pdf (Manual)

The nettheory Package, v2.0
The nettheory package is a collection of routines related to network generation and process theory, including models of power, propinquity, dominance, and diffusion. The primary function of the package is pedagogical, but it may have some research value as well. To use under UNIX, execute the command `R CMD INSTALL /mypath/nettheory_2.0.tar.gz' from your command prompt. Under Windows, install the binary version (nettheory_2.0.zip) into your library directory (see your R documentation). After the installation completes, use `library(nettheory)' from within R to access the nettheory Library. See the R documentation for details.

Note: nettheory requires sna v1.0 or higher.
Files:

Current INDEX and reference manual in Acrobat (PDF) format
nettheory_2.0.tar.gz (Source) and nettheory_2.0.zip (Binary) package files, and nettheory-manual.2.0.pdf (Manual) [Current]
nettheory_1.0.tar.gz (Source) and nettheory_1.0.zip (Binary) package files, and nettheory-manual.1.0.pdf (Manual)

SNA Package Tutorial, v0.0.1 (Obsolete)
This partial draft tutorial is obsolete -- users looking for a package introduction should see my article in volume 24 of the Journal of Statistical Software. See also the sna manuals and online documentation.
Files:
sna.tutorial.0.0.1.txt (Current)

The Metamatrix Package for Organizational Analysis, v0.1
This package of R routines implements the metamatrix approach to the representation and analysis of organizational structure, as articulated by Kathleen Carley, David Krackhardt, Yuquing Ren, and others. This package builds on the SNA package (see above), and the latter must be installed to use many of the former's routines. To use under UNIX, execute the commend `R CMD INSTALL /mypath/metamatrix_0.1.tar.gz' from your command prompt. Under Windows, unzip the package binary (metamatrix_0.1.zip) in your library directory (see the R documentation). After installation completes, use `library(metamatrix)' from within R to access the metamatrix library. See the R documentation for details.
Files:
Current INDEX and reference manual in PostScript and Acrobat (PDF) formats
metamatrix_0.1.tar.gz (Source) and metamatrix_0.1.zip (Binary) package files (Current)

Metamatrix Package Tutorial, v0.1
This tutorial provides a quick and dirty introduction to the analysis of organizational structure using the Metamatrix v0.1 and SNA v0.3 packages. Be sure to get the associated data files, as these are needed to perform the exercises described in the text.
Files:
metamatrix.tutorial.0.1.pdf (Current)
Tutorial data files (Current)

Multivariate Data Analysis

Yet Another Canonical Correlation Analysis Package, v1.0
The yacca ("Yet Another Canonical Correlation Analysis") package is a small library of routines for (as the name implies) canonical correlation analysis (CCA). As compared with R's built-in canonical correlation analysis routine ("cancor"), yacca offers three benefits: (1) it computes a large number of diagnostic and other quantities which are important for the use of CCA in practical settings; (2) it supports native visualization of CCA output (including helio plots); and (3) it scales its output in a more conventional (and, perhaps, intuitive) way than does cancor. Some might also say that it is better documented. To use under UNIX, execute the command `R CMD INSTALL /mypath/yacca_1.0.tar.gz' from your command prompt. Under Windows, install the binary version (yacca_1.0.zip) into your library directory (see your R documentation). After the installation completes, use `library(yacca)' from within R to access the yacca Library. See the R documentation for details.

Files:

Current reference manual in Acrobat (PDF) format
yacca_1.0.tar.gz (Source) and yacca_1.0.zip (Binary) package files, and yacca-manual_1.0.pdf (Manual) [Current]

Bayesian Data Analysis

Routines for Bayesian Conjugate Prior Analysis of Multinomial Likelihood Problems
Not fancy by any stretch of the imagination, but fairly convenient nonetheless: here are some R routines for drawing posterior inferences on multinomial likelihoods given conjugate (dirichlet) priors.
Files:
bayes.multi.0.0.1.R (Current)


Carter Butts

buttsc@uci.edu