---
title: "FoReco (R package): papers citing this CRAN package"
description: "3 papers in the tracked journals link to FoReco (R package) in their Crossref records, the first in 2021; most of them (1) in 2023."
url: https://scholar4ai.com/code/cran-foreco
markdown_url: https://scholar4ai.com/code/cran-foreco.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 FoReco (R package) in their Crossref records, the first in 2021; most of them (1) in 2023. (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)
---

# FoReco (R package): papers linking to it

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

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

## Key findings

- 3 papers in the tracked journals link to FoReco (R package) in their Crossref records, the first in 2021; most of them (1) in 2023.
- By category: AI (2) and Operations Research (1); the journals with the most are Expert Systems with Applications (2) and Computers & Industrial Engineering (1).
- 2 of the papers build on one another: a later paper cites an earlier one that also links FoReco (R package).

## By year

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

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

## Journals

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

| Journal | Papers |
|---|---:|
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 2 |
| [Computers & Industrial Engineering](https://scholar4ai.com/journals/computers-industrial-engineering.md) | 1 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [Hierarchical container throughput forecasting: The value of coherent forecasts in the management of ports operations](https://doi.org/10.1016/j.cie.2022.108651) (Computers & Industrial Engineering, 2022)
  - [Forecast reconciliation in the temporal hierarchy: Special case of intermittent demand with obsolescence](https://doi.org/10.1016/j.eswa.2023.119566) (Expert Systems with Applications, 2023) — cites the paper above

## Papers

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

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2021-05-02 | [A machine learning approach for forecasting hierarchical time series](https://doi.org/10.1016/j.eswa.2021.115102) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Paolo Mancuso, Veronica Piccialli, Antonio M. Sudoso | 74 | cites it |
| 2022-09-14 | [Hierarchical container throughput forecasting: The value of coherent forecasts in the management of ports operations](https://doi.org/10.1016/j.cie.2022.108651) | [Computers & Industrial Engineering](https://scholar4ai.com/journals/computers-industrial-engineering.md) | Kamal Sanguri, Sonali Shankar, Sushil Punia et al. | 18 | cites it |
| 2023-01-20 | [Forecast reconciliation in the temporal hierarchy: Special case of intermittent demand with obsolescence](https://doi.org/10.1016/j.eswa.2023.119566) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Kamal Sanguri, Sabyasachi Patra, Sushil Punia | 5 | 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). FoReco (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-foreco

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