ergm (R package): papers linking to it

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to ergm (R package) (https://CRAN.R-project.org/package=ergm), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

Key findings#

6 papers in the tracked journals link to ergm (R package) in their Crossref records, the first in 2016; most of them (2) in 2019.
By category: Statistics (4) and Tourism and Hospitality (2); the journals with the most are Computational Statistics & Data Analysis (2), Annals of Tourism Research (1) and Computational Statistics (1).
2 of the papers build on one another: a later paper cites an earlier one that also links ergm (R package).

By year#

20162026

Papers linking to ergm (R package) by publication year
Year	Papers
2016	1
2018	2
2019	2
2026	1

Journals#

Journals whose papers link to ergm (R package) most
Journal	Papers
Computational Statistics & Data Analysis	2
Annals of Tourism Research	1
Computational Statistics	1
Information Technology & Tourism	1
Statistics and Computing	1

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Demonstration of exponential random graph models in tourism studies: Is tourism a means of global peace or the bottom line? Annals of Tourism Research, 2018
- Tour guides’ communication ecosystems: an inferential social network analysis approach Information Technology & Tourism, 2018 — cites the paper above

Papers linking to ergm (R package), most cited first
Published	Title	Journal	Authors	Citations	Link
2018-01-03	Demonstration of exponential random graph models in tourism studies: Is tourism a means of global peace or the bottom line?	Annals of Tourism Research	Jalayer Khalilzadeh	58	cites it
2016-10-27	Using contrastive divergence to seed Monte Carlo MLE for exponential-family random graph models	Computational Statistics & Data Analysis	Pavel N. Krivitsky	30	cites it
2019-08-14	A multilayer exponential random graph modelling approach for weighted networks	Computational Statistics & Data Analysis	Alberto Caimo, Isabella Gollini	28	cites it
2018-08-13	Tour guides’ communication ecosystems: an inferential social network analysis approach	Information Technology & Tourism	Ladan Ghahramani, Jalayer Khalilzadeh, Birendra KC	13	cites it
2019-03-11	A note on parallel sampling in Markov graphs	Computational Statistics	Verena Bauer, Karl Fürlinger, Göran Kauermann	1	cites it
2026-05-17	Neural posterior estimation on exponential random graph models: evaluating bias and implementation challenges	Statistics and Computing	Yefeng Fan, Simon Richard White	0	cites it

How this is measured#

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

Cite this page

Scholar4AI. (2026). ergm (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-ergm

@misc{scholar4ai-code-cran-ergm,
  author = {{Scholar4AI}},
  title = {ergm (R package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/cran-ergm}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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