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

Fit, Simulate and Diagnose Exponential-Family Models for Rank-Order Relational Data

Description

ergm.rank is a set of extensions to package ergm to fit and simulate from exponential-family random graph models for networks whose edge weights are ranks. Mainly, it implements the CompleteOrder reference measure for valued ERGMs (Krivitsky 2012; Krivitsky et al. 2023) and provides some rank-order change statistics (search.ergmTerms("ordinal") for a list) (Krivitsky and Butts 2017).

Details

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

All programs derived from this package must cite it.

This package contains functions specific to using ergm to model networks whose dyad values are ranks. Examples include preferences, valued ties reduced to ranks, etc.. These terms have a specialized interpretation, and are therefore generally prefixed by "rank.", though they should take any valued data.

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)

Maintainer: Pavel N. Krivitsky pavel@statnet.org (ORCID)

Other contributors:

References

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

Krivitsky PN, Butts CT (2017). “Exponential-family Random Graph Models for Rank-order Relational Data.” Sociological Methodology, 47(1), 68–112. doi:10.1177/0081175017692623.

Krivitsky PN, Hunter DR, Morris M, Klumb C (2023). “ergm 4: New Features for Analyzing Exponential-Family Random Graph Models.” Journal of Statistical Software, 105(6), 1–44. doi:10.18637/jss.v105.i06.

See Also

Useful links:

[Package ergm.rank version 4.1.1 Index]