---
title: "rvinecopulib (R package): papers citing this CRAN package"
description: "7 papers in the tracked journals link to rvinecopulib (R package) in their Crossref records, the first in 2019; most of them (2) in 2026."
url: https://scholar4ai.com/code/cran-rvinecopulib
markdown_url: https://scholar4ai.com/code/cran-rvinecopulib.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 rvinecopulib (R package) in their Crossref records, the first in 2019; most of them (2) in 2026. (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)
---

# rvinecopulib (R package): papers linking to it

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

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

## Key findings

- 7 papers in the tracked journals link to rvinecopulib (R package) in their Crossref records, the first in 2019; most of them (2) in 2026.
- By category: Statistics (7); the journals with the most are Computational Statistics & Data Analysis (2), Journal of Statistical Theory and Practice (1) and Japanese Journal of Statistics and Data Science (1).
- 3 of the papers build on one another: a later paper cites an earlier one that also links rvinecopulib (R package).

## By year

*Papers linking to rvinecopulib (R package) by publication year*

| Year | Papers |
|---|---:|
| 2019 | 2 |
| 2023 | 1 |
| 2025 | 2 |
| 2026 | 2 |

## Journals

*Journals whose papers link to rvinecopulib (R package) most*

| Journal | Papers |
|---|---:|
| [Computational Statistics & Data Analysis](https://scholar4ai.com/journals/computational-statistics-data-analysis.md) | 2 |
| [Journal of Statistical Theory and Practice](https://scholar4ai.com/journals/journal-of-statistical-theory-and-practice.md) | 1 |
| [Japanese Journal of Statistics and Data Science](https://scholar4ai.com/journals/japanese-journal-of-statistics-and-data-science.md) | 1 |
| [Journal of Multivariate Analysis](https://scholar4ai.com/journals/journal-of-multivariate-analysis.md) | 1 |
| [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | 1 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [Model selection in sparse high-dimensional vine copula models with an application to portfolio risk](https://doi.org/10.1016/j.jmva.2019.03.004) (Journal of Multivariate Analysis, 2019)
  - [Vine Copula based Portfolio Level Conditional Risk Measure Forecasting](https://doi.org/10.1016/j.ecosta.2023.08.002) (Econometrics and Statistics, 2023) — cites the paper above
  - [Derandomized Truncated D-vine Copula Knockoffs with e-values to control the false discovery rate](https://doi.org/10.1007/s00180-024-01587-x) (Computational Statistics, 2025) — cites the paper above

## Papers

*Papers linking to rvinecopulib (R package), most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2019-03-18 | [Model selection in sparse high-dimensional vine copula models with an application to portfolio risk](https://doi.org/10.1016/j.jmva.2019.03.004) | [Journal of Multivariate Analysis](https://scholar4ai.com/journals/journal-of-multivariate-analysis.md) | Thomas Nagler, Christian Bumann, Claudia Czado | 72 | cites it |
| 2019-07-18 | [Common sampling orders of regular vines with application to model selection](https://doi.org/10.1016/j.csda.2019.106811) | [Computational Statistics & Data Analysis](https://scholar4ai.com/journals/computational-statistics-data-analysis.md) | Kailun Zhu, Dorota Kurowicka, Gabriela F. Nane | 7 | cites it |
| 2023-08-21 | [Vine Copula based Portfolio Level Conditional Risk Measure Forecasting](https://doi.org/10.1016/j.ecosta.2023.08.002) | [Econometrics and Statistics](https://scholar4ai.com/journals/econometrics-and-statistics.md) | Emanuel Sommer, Karoline Bax, Claudia Czado | 6 | cites it |
| 2025-01-20 | [Derandomized Truncated D-vine Copula Knockoffs with e-values to control the false discovery rate](https://doi.org/10.1007/s00180-024-01587-x) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Alejandro Román Vásquez, José Ulises Márquez Urbina, Graciela González-Farı́as et al. | 1 | cites it |
| 2025-12-11 | [On multivariate binary outcomes copulas-regression problem](https://doi.org/10.1007/s42081-025-00322-0) | [Japanese Journal of Statistics and Data Science](https://scholar4ai.com/journals/japanese-journal-of-statistics-and-data-science.md) | Youssef Handi, Karim Oualkacha, Mhamed Mesfioui | 1 | cites it |
| 2026-03-24 | [Optimising covariate allocation at design stage using fisher information matrix for non-linear mixed effects models in pharmacometrics](https://doi.org/10.1016/j.csda.2026.108379) | [Computational Statistics & Data Analysis](https://scholar4ai.com/journals/computational-statistics-data-analysis.md) | Lucie Fayette, Karl Brendel, France Mentré | 0 | cites it |
| 2026-04-28 | [Inference Based on Copulas for Quantile and Expectile for Binary Regression](https://doi.org/10.1007/s42519-026-00577-0) | [Journal of Statistical Theory and Practice](https://scholar4ai.com/journals/journal-of-statistical-theory-and-practice.md) | Youssef Handi, Karim Oualkacha, Mhamed Mesfioui | 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). rvinecopulib (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-rvinecopulib

```bibtex
@misc{scholar4ai-code-cran-rvinecopulib,
  author = {{Scholar4AI}},
  title = {rvinecopulib (R package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/cran-rvinecopulib}},
  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/).