GGally (R package): papers linking to it

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

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to GGally (R package) (https://CRAN.R-project.org/package=GGally), 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#

7 papers in the tracked journals link to GGally (R package) in their Crossref records, the first in 2018; most of them (3) in 2023.
By category: Statistics (3), Economics (2) and Higher Education and Research (1); the journals with the most are World Development (1), Journal of Economic Interaction and Coordination (1) and Scientometrics (1).

By year#

20182023

Papers linking to GGally (R package) by publication year
Year	Papers
2018	1
2019	1
2020	1
2021	1
2023	3

Journals#

Journals whose papers link to GGally (R package) most
Journal	Papers
World Development	1
Journal of Economic Interaction and Coordination	1
Scientometrics	1
Computational Statistics & Data Analysis	1
Japanese Journal of Statistics and Data Science	1

Papers linking to GGally (R package), most cited first
Published	Title	Journal	Authors	Citations	Link
2021-06-17	Knowledge gaps in Latin America and the Caribbean and economic development	World Development	Pablo Jarrín–V, Fander Falconí, Pedro Cango et al.	19	cites it
2023-04-13	Sectoral integration on an emerging stock market: a multi-scale approach	Journal of Economic Interaction and Coordination	Kingstone Nyakurukwa, Yudhvir Seetharam	5	cites it
2020-03-14	An exploration of gender gap using advanced data science tools: actuarial research community	Scientometrics	Mengyu Yu, Mazie Krehbiel, Samantha Thompson et al.	4	cites it
2019-02-05	Soul of the community: an attempt to assess attachment to a community	Computational Statistics	Anna Quach, Jürgen Symanzik, Nicole Forsgren	3	cites it
2018-07-29	Visualizing data through curvilinear representations of matrices	Computational Statistics & Data Analysis	Daniel K. Sewell	2	cites it
2023-07-27	Statistical modeling of Peromyscus maniculatus (deer mouse) amounts per trap with spatiotemporal data	Japanese Journal of Statistics and Data Science	Hsin‐Hsiung Huang, Qing He	2	cites it
2023-12-26	CSViz: Class Separability Visualization for high-dimensional datasets	Applied Intelligence	Marina Cuesta, Carmen Lancho, Alberto Fernández-Isabel et al.	1	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). GGally (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-ggally

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

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