---
title: "hts (R package): papers citing this CRAN package"
description: "5 papers in the tracked journals link to hts (R package) in their Crossref records, the first in 2019; most of them (3) in 2019."
url: https://scholar4ai.com/code/cran-hts
markdown_url: https://scholar4ai.com/code/cran-hts.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 hts (R package) in their Crossref records, the first in 2019; most of them (3) in 2019. (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)
---

# hts (R package): papers linking to it

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

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

## Key findings

- 5 papers in the tracked journals link to hts (R package) in their Crossref records, the first in 2019; most of them (3) in 2019.
- By category: Economics (2), AI (2) and Operations Research (1); the journals with the most are International Journal of Forecasting (2), Computers & Industrial Engineering (1) and Machine Learning (1).

## By year

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

| Year | Papers |
|---|---:|
| 2019 | 3 |
| 2022 | 2 |

## Journals

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

| Journal | Papers |
|---|---:|
| [International Journal of Forecasting](https://scholar4ai.com/journals/international-journal-of-forecasting.md) | 2 |
| [Computers & Industrial Engineering](https://scholar4ai.com/journals/computers-industrial-engineering.md) | 1 |
| [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | 1 |
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 1 |

## Papers

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

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2019-06-27 | [Hierarchical time series forecasting via Support Vector Regression in the European Travel Retail Industry](https://doi.org/10.1016/j.eswa.2019.06.060) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Juan Pablo Karmy, Sebastián Maldonado | 86 | cites it |
| 2019-07-16 | [The M4 forecasting competition – A practitioner’s view](https://doi.org/10.1016/j.ijforecast.2019.02.013) | [International Journal of Forecasting](https://scholar4ai.com/journals/international-journal-of-forecasting.md) | Chris Fry, Michael Brundage | 34 | cites it |
| 2022-01-14 | [Model selection in reconciling hierarchical time series](https://doi.org/10.1007/s10994-021-06126-z) | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | Mahdi Abolghasemi, Rob J. Hyndman, Evangelos Spiliotis et al. | 25 | 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 |
| 2019-03-12 | [Data visualization and forecast combination for probabilistic load forecasting in GEFCom2017 final match](https://doi.org/10.1016/j.ijforecast.2019.02.004) | [International Journal of Forecasting](https://scholar4ai.com/journals/international-journal-of-forecasting.md) | Julian de Hoog, Khalid Abdulla | 1 | 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). hts (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-hts

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