---
title: "quantregForest (R package): papers citing it"
description: "8 papers in the tracked journals link to quantregForest (R package) in their Crossref records, the first in 2018; most of them (2) in 2026."
url: https://scholar4ai.com/code/cran-quantregforest
markdown_url: https://scholar4ai.com/code/cran-quantregforest.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "8 papers in the tracked journals link to quantregForest (R package) in their Crossref records, the first in 2018; 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)
---

# quantregForest (R package): papers linking to it

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

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

## Key findings

- 8 papers in the tracked journals link to quantregForest (R package) in their Crossref records, the first in 2018; most of them (2) in 2026.
- By category: Economics (3), AI (2) and Operations Research (1); the journals with the most are Mineral Economics (1), Land Use Policy (1) and Transportation Research Part C Emerging Technologies (1).

## By year

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

| Year | Papers |
|---|---:|
| 2018 | 2 |
| 2020 | 1 |
| 2022 | 1 |
| 2024 | 2 |
| 2026 | 2 |

## Journals

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

| Journal | Papers |
|---|---:|
| [Mineral Economics](https://scholar4ai.com/journals/mineral-economics.md) | 1 |
| [Land Use Policy](https://scholar4ai.com/journals/land-use-policy.md) | 1 |
| [Transportation Research Part C Emerging Technologies](https://scholar4ai.com/journals/transportation-research-part-c-emerging-technologies.md) | 1 |
| [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | 1 |
| [Finance research letters](https://scholar4ai.com/journals/finance-research-letters.md) | 1 |

## Papers

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

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2018-05-21 | [Comparison of intraday probabilistic forecasting of solar irradiance using only endogenous data](https://doi.org/10.1016/j.ijforecast.2018.02.003) | [International Journal of Forecasting](https://scholar4ai.com/journals/international-journal-of-forecasting.md) | Mathieu David, Luis Mazorra-Aguiar, Philippe Lauret | 69 | cites it |
| 2024-02-23 | [Data-driven multinomial random forest: a new random forest variant with strong consistency](https://doi.org/10.1186/s40537-023-00874-6) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | Junhao Chen, Xueli Wang, Fei Lei | 38 | cites it |
| 2018-08-20 | [The predictive value of inequality measures for stock returns: An analysis of long-span UK data using quantile random forests](https://doi.org/10.1016/j.frl.2018.08.013) | [Finance research letters](https://scholar4ai.com/journals/finance-research-letters.md) | Rangan Gupta, Christian Pierdzioch, Andrew J. Vivian et al. | 29 | 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 |
| 2020-02-25 | [A class-specific soft voting framework for customer booking prediction in on-demand transport](https://doi.org/10.1016/j.trc.2020.02.010) | [Transportation Research Part C Emerging Technologies](https://scholar4ai.com/journals/transportation-research-part-c-emerging-technologies.md) | Minh Kieu, Yuming Ou, Long T. Truong et al. | 13 | cites it |
| 2024-08-22 | [Development of an adaptive reliability analysis framework for reinforced concrete frame structures using uncertainty quantification](https://doi.org/10.1007/s10489-024-05731-4) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Truong-Thang Nguyen, Viet-Hung Dang, Manh-Hung Ha et al. | 4 | cites it |
| 2026-06-26 | [Transfer learning for causal forests](https://doi.org/10.1007/s11222-026-10919-4) | [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | Bérénice-Alexia Jocteur, Véronique Maume‐Deschamps, Pierre Ribereau | 0 | cites it |
| 2026-10-19 | [Driving renewable energy minerals: the roles of innovation, policy uncertainty, and environmental stringency in China](https://doi.org/10.1007/s13563-026-00708-w) | [Mineral Economics](https://scholar4ai.com/journals/mineral-economics.md) | Zohaib Hassan, Deyi Xu, Shah Abbas et al. | 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). quantregForest (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-quantregforest

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