‘tergm’ is part of the Statnet suite of packages. If you are using the ‘tergm’ package for research that will be published, we request that you acknowledge this by citing the following. For BibTeX format, use toBibtex(citation("tergm")).

Krivitsky P, Handcock M (2022). tergm: Fit, Simulate and Diagnose Models for Network Evolution Based on Exponential-Family Random Graph Models. The Statnet Project (https://statnet.org). R package version 4.1.0, https://CRAN.R-project.org/package=tergm.

Krivitsky P, Handcock M (2014). “A Separable Model for Dynamic Networks.” Journal of the Royal Statistical Society, Series B, 76(1), 29-46. doi:10.1111/rssb.12014.

Carnegie N, Krivitsky P, Hunter D, Goodreau S (2015). “An Approximation Method for Improving Dynamic Network Model Fitting.” Journal of Computational and Graphical Statistics, 24(2), 502-519. doi:10.1080/10618600.2014.903087.

We have invested a lot of time and effort in creating the Statnet suite of packages for use by other researchers. Please cite it in all papers where it is used. The package ‘tergm’ is distributed under the terms of the license GPL-3 + file LICENSE.

Corresponding BibTeX entries:

  @Manual{,
    author = {Pavel N. Krivitsky and Mark S. Handcock},
    title = {tergm: Fit, Simulate and Diagnose Models for Network
      Evolution Based on Exponential-Family Random Graph Models},
    organization = {The Statnet Project (\url{https://statnet.org})},
    year = {2022},
    note = {R package version 4.1.0},
    url = {https://CRAN.R-project.org/package=tergm},
  }

  @Article{,
    author = {Pavel N. Krivitsky and Mark S. Handcock},
    title = {A Separable Model for Dynamic Networks},
    journal = {Journal of the Royal Statistical Society, Series B},
    year = {2014},
    volume = {76},
    number = {1},
    pages = {29-46},
    doi = {10.1111/rssb.12014},
  }

  @Article{,
    author = {Nicole Bohme Carnegie and Pavel N. Krivitsky and David R.
      Hunter and Steven M. Goodreau},
    title = {An Approximation Method for Improving Dynamic Network
      Model Fitting},
    journal = {Journal of Computational and Graphical Statistics},
    year = {2015},
    volume = {24},
    number = {2},
    pages = {502-519},
    doi = {10.1080/10618600.2014.903087},
  }