ergm.count-package {ergm.count}R Documentation

Fit, Simulate and Diagnose Exponential-Family Models for Networks with Count Edges

Description

ergm.count is a set of extensions to package ergm to fit and simulate from exponential-family random graph models for networks whose edge weights are counts. For a list of functions type help(package='ergm') and help(package='ergm.count')

Details

Mainly, it implements Poisson, binomial, geometric, and discrete uniform dyadwise reference measures for valued ERGMs (documented here), and provides some count-specific change statistics (documented here).

For a complete list of the functions, use library(help="ergm") and library(help="ergm.count") or read the rest of the manual.

When publishing results obtained using this package, please cite the original authors as described in citation(package="ergm.count").

All programs derived from this package must cite it.

This package contains functions specific to using ergm to model networks whose dyad values are counts. Examples include counts of conversations, messages, and other interactions.

In particular, this package implements the Poisson, geometric, binomial, and discrete uniform reference measures (documented in ergm-references) for use by ergm and simulate.ergm to fit models from this family, as well as statistics specific to modeling counts, such as the CMP for the Conway-Maxwell-Poisson Distribution.

For detailed information on how to download and install the software, go to the Statnet project website: https://statnet.org. A tutorial, support newsgroup, references and links to further resources are provided there.

Author(s)

Pavel N. Krivitsky pavel@statnet.org

References

Handcock MS, Hunter DR, Butts CT, Goodreau SG, Krivitsky PN and Morris M (2012). _Fit, Simulate and Diagnose Exponential-Family Models for Networks_. Version 3.1. Project home page at <URL: https://www.statnet.org>, <URL: CRAN.R-project.org/package=ergm>.

Krivitsky PN (2012). Exponential-Family Random Graph Models for Valued Networks. Electronic Journal of Statistics, 2012, 6, 1100-1128. doi: 10.1214/12-EJS696

See Also

ergm-terms, ergm-references


[Package ergm.count version 4.0.2 Index]