---
title: "randomForest (R package): papers citing this CRAN package"
description: "9 papers in the tracked journals link to randomForest (R package) in their Crossref records, the first in 2017; most of them (3) in 2021."
url: https://scholar4ai.com/code/cran-randomforest
markdown_url: https://scholar4ai.com/code/cran-randomforest.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "9 papers in the tracked journals link to randomForest (R package) in their Crossref records, the first in 2017; most of them (3) in 2021. (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)
---

# randomForest (R package): papers linking to it

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

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

## Key findings

- 9 papers in the tracked journals link to randomForest (R package) in their Crossref records, the first in 2017; most of them (3) in 2021.
- By category: Information Systems (2), Statistics (2) and Economics (1); the journals with the most are Land Use Policy (1), Journal of Open Innovation Technology Market and Complexity (1) and Electronic Markets (1).

## By year

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

| Year | Papers |
|---|---:|
| 2017 | 1 |
| 2018 | 1 |
| 2019 | 1 |
| 2021 | 3 |
| 2022 | 1 |
| 2023 | 1 |
| 2025 | 1 |

## Journals

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

| Journal | Papers |
|---|---:|
| [Land Use Policy](https://scholar4ai.com/journals/land-use-policy.md) | 1 |
| [Journal of Open Innovation Technology Market and Complexity](https://scholar4ai.com/journals/journal-of-open-innovation-technology-market-and-complexity.md) | 1 |
| [Electronic Markets](https://scholar4ai.com/journals/electronic-markets.md) | 1 |
| [Business & Information Systems Engineering](https://scholar4ai.com/journals/business-information-systems-engineering.md) | 1 |
| [Scientometrics](https://scholar4ai.com/journals/scientometrics.md) | 1 |

## Papers

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

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2017-07-27 | [Bayesian Additive Regression Trees using Bayesian model averaging](https://doi.org/10.1007/s11222-017-9767-1) | [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | Belinda Hernández, Adrian E. Raftery, Stephen R. Pennington et al. | 67 | cites it |
| 2019-11-20 | [Distributional regression for demand forecasting in e-grocery](https://doi.org/10.1016/j.ejor.2019.11.029) | [European Journal of Operational Research](https://scholar4ai.com/journals/european-journal-of-operational-research.md) | Matthias Ulrich, Hermann Jahnke, Roland Langrock et al. | 56 | cites it |
| 2018-03-17 | [Enhancing energy efficiency in the residential sector with smart meter data analytics](https://doi.org/10.1007/s12525-018-0290-9) | [Electronic Markets](https://scholar4ai.com/journals/electronic-markets.md) | Konstantin Hopf, Mariya Sodenkamp, Thorsten Staake | 47 | cites it |
| 2021-03-10 | [Benchmarking Energy Quantification Methods to Predict Heating Energy Performance of Residential Buildings in Germany](https://doi.org/10.1007/s12599-021-00691-2) | [Business & Information Systems Engineering](https://scholar4ai.com/journals/business-information-systems-engineering.md) | Simon Wenninger, Christian Wiethe | 47 | cites it |
| 2022-06-09 | [Mass appraisal as affordable public policy: Open data and machine learning for mapping urban land values](https://doi.org/10.1016/j.landusepol.2022.106211) | [Land Use Policy](https://scholar4ai.com/journals/land-use-policy.md) | Juan Pablo Carranza, Mario Andrés Piumetto, Carlos María Lucca et al. | 26 | cites it |
| 2023-01-09 | [Ten reasons why research collaborations succeed—a random forest approach](https://doi.org/10.1007/s11192-022-04629-7) | [Scientometrics](https://scholar4ai.com/journals/scientometrics.md) | Malte Hückstädt | 16 | cites it |
| 2021-01-12 | [Technology Integration and Analysis Using Boosting and Ensemble](https://doi.org/10.3390/joitmc7010027) | [Journal of Open Innovation Technology Market and Complexity](https://scholar4ai.com/journals/journal-of-open-innovation-technology-market-and-complexity.md) | Sunghae Jun | 8 | cites it |
| 2021-02-26 | [Interpreting the black box of supervised learning models: Visualizing the impacts of features on prediction](https://doi.org/10.1007/s10489-021-02255-z) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Xiaohang Zhang, Yuan Wang, Zhengren Li | 6 | cites it |
| 2025-10-29 | [Combining variable screening methods for model averaging in high-dimensional data analysis](https://doi.org/10.1007/s10463-025-00961-w) | [Annals of the Institute of Statistical Mathematics](https://scholar4ai.com/journals/annals-of-the-institute-of-statistical-mathematics.md) | Zhihao Zhao, Yuhong Yang, Li Wen | 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). randomForest (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-randomforest

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