---
title: "GGally (R package): papers citing this CRAN package"
description: "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."
url: https://scholar4ai.com/code/cran-ggally
markdown_url: https://scholar4ai.com/code/cran-ggally.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "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. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# GGally (R package): papers linking to it

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.

- CRAN
- https://CRAN.R-project.org/package=GGally

All repositories: https://scholar4ai.com/code.md

## 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

*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](https://scholar4ai.com/journals/world-development.md) | 1 |
| [Journal of Economic Interaction and Coordination](https://scholar4ai.com/journals/journal-of-economic-interaction-and-coordination.md) | 1 |
| [Scientometrics](https://scholar4ai.com/journals/scientometrics.md) | 1 |
| [Computational Statistics & Data Analysis](https://scholar4ai.com/journals/computational-statistics-data-analysis.md) | 1 |
| [Japanese Journal of Statistics and Data Science](https://scholar4ai.com/journals/japanese-journal-of-statistics-and-data-science.md) | 1 |

## Papers

*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](https://doi.org/10.1016/j.worlddev.2021.105602) | [World Development](https://scholar4ai.com/journals/world-development.md) | 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](https://doi.org/10.1007/s11403-023-00383-y) | [Journal of Economic Interaction and Coordination](https://scholar4ai.com/journals/journal-of-economic-interaction-and-coordination.md) | Kingstone Nyakurukwa, Yudhvir Seetharam | 5 | cites it |
| 2020-03-14 | [An exploration of gender gap using advanced data science tools: actuarial research community](https://doi.org/10.1007/s11192-020-03412-w) | [Scientometrics](https://scholar4ai.com/journals/scientometrics.md) | 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](https://doi.org/10.1007/s00180-019-00866-2) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Anna Quach, Jürgen Symanzik, Nicole Forsgren | 3 | cites it |
| 2018-07-29 | [Visualizing data through curvilinear representations of matrices](https://doi.org/10.1016/j.csda.2018.07.010) | [Computational Statistics & Data Analysis](https://scholar4ai.com/journals/computational-statistics-data-analysis.md) | Daniel K. Sewell | 2 | cites it |
| 2023-07-27 | [Statistical modeling of Peromyscus maniculatus (deer mouse) amounts per trap with spatiotemporal data](https://doi.org/10.1007/s42081-023-00212-3) | [Japanese Journal of Statistics and Data Science](https://scholar4ai.com/journals/japanese-journal-of-statistics-and-data-science.md) | Hsin‐Hsiung Huang, Qing He | 2 | cites it |
| 2023-12-26 | [CSViz: Class Separability Visualization for high-dimensional datasets](https://doi.org/10.1007/s10489-023-05149-4) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 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

```bibtex
@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}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).