---
title: "mclust (R package): papers citing this CRAN package"
description: "5 papers in the tracked journals link to mclust (R package) in their Crossref records, the first in 2019; most of them (1) in 2024."
url: https://scholar4ai.com/code/cran-mclust
markdown_url: https://scholar4ai.com/code/cran-mclust.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "5 papers in the tracked journals link to mclust (R package) in their Crossref records, the first in 2019; 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)
---

# mclust (R package): papers linking to it

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

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

## Key findings

- 5 papers in the tracked journals link to mclust (R package) in their Crossref records, the first in 2019; most of them (1) in 2024.
- By category: Statistics (3), Operations Research (1) and AI (1); the journals with the most are Computational Statistics (2), Transportation Research Part A Policy and Practice (1) and Econometrics and Statistics (1).

## By year

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

| Year | Papers |
|---|---:|
| 2019 | 1 |
| 2021 | 1 |
| 2022 | 1 |
| 2023 | 1 |
| 2024 | 1 |

## Journals

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

| Journal | Papers |
|---|---:|
| [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | 2 |
| [Transportation Research Part A Policy and Practice](https://scholar4ai.com/journals/transportation-research-part-a-policy-and-practice.md) | 1 |
| [Econometrics and Statistics](https://scholar4ai.com/journals/econometrics-and-statistics.md) | 1 |
| [Data Mining and Knowledge Discovery](https://scholar4ai.com/journals/data-mining-and-knowledge-discovery.md) | 1 |

## Papers

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

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2024-08-07 | [Towards understanding travel in the digital age: A cross-dimensional one-week diary of individual virtual and physical activities in Indonesian cities](https://doi.org/10.1016/j.tra.2024.104195) | [Transportation Research Part A Policy and Practice](https://scholar4ai.com/journals/transportation-research-part-a-policy-and-practice.md) | Muhamad Rizki, Tri Basuki Joewono, Yusak Octavius Susilo | 9 | cites it |
| 2019-02-20 | [Dynamic detection of anomalous regions within distributed acoustic sensing data streams using locally stationary wavelet time series](https://doi.org/10.1007/s10618-018-00608-w) | [Data Mining and Knowledge Discovery](https://scholar4ai.com/journals/data-mining-and-knowledge-discovery.md) | Rebecca Wilson, Idris Arthur Eckley, Matthew A. Nunes et al. | 6 | cites it |
| 2022-04-04 | [Smallest covering regions and highest density regions for discrete distributions](https://doi.org/10.1007/s00180-021-01172-6) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Ben O’Neill | 4 | cites it |
| 2023-02-06 | [Analyzing cellwise weighted data](https://doi.org/10.1016/j.ecosta.2023.01.007) | [Econometrics and Statistics](https://scholar4ai.com/journals/econometrics-and-statistics.md) | Peter J. Rousseeuw | 3 | cites it |
| 2021-08-05 | [Computing highest density regions for continuous univariate distributions with known probability functions](https://doi.org/10.1007/s00180-021-01133-z) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Ben O’Neill | 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). mclust (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-mclust

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