rmarkdown (R package): papers linking to it

CRAN · CRAN.R-project.org/package=rmarkdown

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to rmarkdown (R package) (https://CRAN.R-project.org/package=rmarkdown), 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 rmarkdown (R package) in their Crossref records, the first in 2018; most of them (2) in 2019.
By category: AI (4), Economics (1) and Statistics (1); the journals with the most are Neural Computing and Applications (2), Energy Policy (1) and Statistical Papers (1).

By year#

20182026

Papers linking to rmarkdown (R package) by publication year
Year	Papers
2018	1
2019	2
2020	1
2025	1
2026	1

Journals#

Journals whose papers link to rmarkdown (R package) most
Journal	Papers
Neural Computing and Applications	2
Energy Policy	1
Statistical Papers	1
Neural Networks	1
Language Resources and Evaluation	1

Papers linking to rmarkdown (R package), most cited first
Published	Title	Journal	Authors	Citations	Link
2020-07-06	Super ensemble learning for daily streamflow forecasting: large-scale demonstration and comparison with multiple machine learning algorithms	Neural Computing and Applications	Hristos Tyralis, Georgia Papacharalampous, Andreas Langousis	177	cites it
2019-03-06	Onshore wind and the likelihood of planning acceptance: Learning from a Great Britain context	Energy Policy	Michael Harper, Ben Anderson, Patrick A.B. James et al.	61	cites it
2019-04-08	Beyond lexical frequencies: using R for text analysis in the digital humanities	Language Resources and Evaluation	Taylor Arnold, Nicolas Ballier, Paula Lissón et al.	10	cites it
2018-05-30	A web-oriented expert system for planning hurdles race training programmes	Neural Computing and Applications	Krzysztof Przednówek, Krzysztof Wiktorowicz, Tomasz Krzeszowski et al.	7	cites it
2025-03-05	Deep Huber quantile regression networks	Neural Networks	Hristos Tyralis, Georgia Papacharalampous, Nilay Doğulu et al.	7	cites it
2026-04-11	Cor: an R package for optimal subset selection in distributed estimation	Statistical Papers	Di Chang, Guangbao Guo, Lixing Zhu	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). rmarkdown (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-rmarkdown

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

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