---
title: "COMPoissonReg (R package): papers citing this CRAN package"
description: "3 papers in the tracked journals link to COMPoissonReg (R package) in their Crossref records, the first in 2017; most of them (1) in 2024."
url: https://scholar4ai.com/code/cran-compoissonreg
markdown_url: https://scholar4ai.com/code/cran-compoissonreg.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "3 papers in the tracked journals link to COMPoissonReg (R package) in their Crossref records, the first in 2017; most of them (1) in 2024. (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)
---

# COMPoissonReg (R package): papers linking to it

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

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

## Key findings

- 3 papers in the tracked journals link to COMPoissonReg (R package) in their Crossref records, the first in 2017; most of them (1) in 2024.
- By category: Statistics (3); the journals with the most are Statistics and Computing (2) and Computational Statistics (1).
- 3 of the papers build on one another: a later paper cites an earlier one that also links COMPoissonReg (R package).

## By year

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

| Year | Papers |
|---|---:|
| 2017 | 1 |
| 2023 | 1 |
| 2024 | 1 |

## Journals

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

| Journal | Papers |
|---|---:|
| [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | 2 |
| [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | 1 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [Efficient Bayesian inference for COM-Poisson regression models](https://doi.org/10.1007/s11222-017-9750-x) (Statistics and Computing, 2017)
  - [A fast look-up method for Bayesian mean-parameterised Conway–Maxwell–Poisson regression models](https://doi.org/10.1007/s11222-023-10244-0) (Statistics and Computing, 2023) — cites the paper above
  - [A simple algorithm for computing the probabilities of count models based on pure birth processes](https://doi.org/10.1007/s00180-024-01491-4) (Computational Statistics, 2024) — cites the paper above

## Papers

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

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2017-04-24 | [Efficient Bayesian inference for COM-Poisson regression models](https://doi.org/10.1007/s11222-017-9750-x) | [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | Charalampos Chanialidis, Ludger Evers A, Tereza Neocleous et al. | 37 | cites it |
| 2023-05-18 | [A fast look-up method for Bayesian mean-parameterised Conway–Maxwell–Poisson regression models](https://doi.org/10.1007/s11222-023-10244-0) | [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | Pete Philipson, Alan Huang | 8 | cites it |
| 2024-04-10 | [A simple algorithm for computing the probabilities of count models based on pure birth processes](https://doi.org/10.1007/s00180-024-01491-4) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Mongkol Hunkrajok, Wanrudee Skulpakdee | 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). COMPoissonReg (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-compoissonreg

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