---
title: "fpp2 (R package): papers citing this CRAN package"
description: "25 papers in the tracked journals link to fpp2 (R package) in their Crossref records, the first in 2019; most of them (5) in 2026."
url: https://scholar4ai.com/code/cran-fpp2
markdown_url: https://scholar4ai.com/code/cran-fpp2.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "25 papers in the tracked journals link to fpp2 (R package) in their Crossref records, the first in 2019; most of them (5) 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)
---

# fpp2 (R package): papers linking to it

Research papers in the 480 tracked journals that link to fpp2 (R package) (https://CRAN.R-project.org/package=fpp2), 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=fpp2

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

## Key findings

- 25 papers in the tracked journals link to fpp2 (R package) in their Crossref records, the first in 2019; most of them (5) in 2026.
- By category: AI (10), Operations Research (5) and Economics (4); the journals with the most are Applied Intelligence (3), Letters in Spatial and Resource Sciences (2) and Neural Computing and Applications (2).
- 2 of the papers build on one another: a later paper cites an earlier one that also links fpp2 (R package).

## By year

*Papers linking to fpp2 (R package) by publication year*

| Year | Papers |
|---|---:|
| 2019 | 1 |
| 2020 | 2 |
| 2021 | 3 |
| 2022 | 2 |
| 2023 | 3 |
| 2024 | 4 |
| 2025 | 5 |
| 2026 | 5 |

## Journals

*Journals whose papers link to fpp2 (R package) most*

| Journal | Papers |
|---|---:|
| [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 3 |
| [Letters in Spatial and Resource Sciences](https://scholar4ai.com/journals/letters-in-spatial-and-resource-sciences.md) | 2 |
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 2 |
| [Computational Economics](https://scholar4ai.com/journals/computational-economics.md) | 2 |
| [Computers & Industrial Engineering](https://scholar4ai.com/journals/computers-industrial-engineering.md) | 2 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [The future of regional inequalities: an ARIMA forecast](https://doi.org/10.1007/s12076-024-00379-7) (Letters in Spatial and Resource Sciences, 2024)
  - [The future of urban hierearchy and Zipf law: ARIMA and BATS forecasting](https://doi.org/10.1007/s12076-025-00408-z) (Letters in Spatial and Resource Sciences, 2025) — cites the paper above

## Papers

*Papers linking to fpp2 (R package), most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2022-12-02 | [Forecast evaluation for data scientists: common pitfalls and best practices](https://doi.org/10.1007/s10618-022-00894-5) | [Data Mining and Knowledge Discovery](https://scholar4ai.com/journals/data-mining-and-knowledge-discovery.md) | Hansika Hewamalage, Klaus Ackermann, Christoph Bergmeir | 296 | cites it |
| 2020-02-22 | [Demand forecasting in supply chain: The impact of demand volatility in the presence of promotion](https://doi.org/10.1016/j.cie.2020.106380) | [Computers & Industrial Engineering](https://scholar4ai.com/journals/computers-industrial-engineering.md) | Mahdi Abolghasemi, Eric J. Beh, Garth Tarr et al. | 202 | cites it |
| 2020-07-04 | [Time-series forecasting of Bitcoin prices using high-dimensional features: a machine learning approach](https://doi.org/10.1007/s00521-020-05129-6) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Mohammed Mudassir, Shada Bennbaia, Devrim Ünal et al. | 182 | cites it |
| 2021-08-14 | [Inventory – forecasting: Mind the gap](https://doi.org/10.1016/j.ejor.2021.07.040) | [European Journal of Operational Research](https://scholar4ai.com/journals/european-journal-of-operational-research.md) | Thanos E. Goltsos, Aris A Syntetos, Christoph  H. Glock et al. | 115 | cites it |
| 2021-06-03 | [Forecasting air passenger numbers with a GVAR model](https://doi.org/10.1016/j.annals.2021.103252) | [Annals of Tourism Research](https://scholar4ai.com/journals/annals-of-tourism-research.md) | Ulrich Gunter, Bozana Zekan | 47 | cites it |
| 2023-01-23 | [Export- and import-based economic models for predicting global trade using deep learning](https://doi.org/10.1016/j.eswa.2023.119590) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Cheng‐Hong Yang, Cheng-Feng Lee, Po-Yin Chang | 38 | cites it |
| 2021-08-21 | [Out-of-time cross-validation strategies for classification in the presence of dataset shift](https://doi.org/10.1007/s10489-021-02735-2) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Sebastián Maldonado, Julio López, Andrés Iturriaga | 24 | cites it |
| 2019-07-26 | [SAZED: parameter-free domain-agnostic season length estimation in time series data](https://doi.org/10.1007/s10618-019-00645-z) | [Data Mining and Knowledge Discovery](https://scholar4ai.com/journals/data-mining-and-knowledge-discovery.md) | Maximilian Toller, Tiago Santos, Roman Kern | 18 | cites it |
| 2024-07-19 | [Shaping closed-loop supply chain dynamics: Mitigating the bullwhip effect and improving customer satisfaction in production systems with material reuse](https://doi.org/10.1016/j.cie.2024.110407) | [Computers & Industrial Engineering](https://scholar4ai.com/journals/computers-industrial-engineering.md) | Carmen Liping Fernández-Arribas, Borja Ponte, Isabel Fernández | 17 | cites it |
| 2025-05-07 | [A Novel Hybrid Ensemble Framework for Stock Price Prediction: Combining Bagging, Boosting, Dagging, and Stacking](https://doi.org/10.1007/s10614-025-10979-0) | [Computational Economics](https://scholar4ai.com/journals/computational-economics.md) | Aqib Gul | 12 | cites it |
| 2023-01-25 | [Correlated product of experts for sparse Gaussian process regression](https://doi.org/10.1007/s10994-022-06297-3) | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | Manuel Schürch, Dario Azzimonti, Alessio Benavoli et al. | 11 | cites it |
| 2023-12-29 | [Effectiveness of ATM withdrawal forecasting methods under different market conditions](https://doi.org/10.1016/j.techfore.2023.123089) | [Technological Forecasting and Social Change](https://scholar4ai.com/journals/technological-forecasting-and-social-change.md) | Marcin Suder, Henryk Gurgul, Belém Barbosa et al. | 8 | cites it |
| 2024-07-02 | [Forecasting the waste production hierarchical time series with correlation structure](https://doi.org/10.1007/s11081-024-09898-0) | [Optimization and Engineering](https://scholar4ai.com/journals/optimization-and-engineering.md) | Ivan Eryganov, Martin Rosecký, Radovan Šomplák et al. | 7 | cites it |
| 2026-02-01 | [FinBERT-BiLSTM: a deep learning model for predicting volatile cryptocurrency market prices using market sentiment dynamics](https://doi.org/10.1007/s10489-026-07086-4) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Mabsur Fatin Bin Hossain, Lubna Zahan Lamia, Md Mahmudur Rahman et al. | 6 | cites it |
| 2024-02-24 | [Measuring regularity of human physical activities with entropy models](https://doi.org/10.1186/s40537-024-00891-z) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | Keqin Shi, Zhen Chen, Weiqiang Sun et al. | 5 | cites it |
| 2024-05-06 | [The future of regional inequalities: an ARIMA forecast](https://doi.org/10.1007/s12076-024-00379-7) | [Letters in Spatial and Resource Sciences](https://scholar4ai.com/journals/letters-in-spatial-and-resource-sciences.md) | Hasan Engìn Duran | 5 | cites it |
| 2025-05-08 | [MSR-GAN: multi-scales decomposition representations for unsupervised anomaly detection](https://doi.org/10.1007/s10489-025-06606-y) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Dongwei Xu, Tianhao Xia, Jiaye Hou et al. | 3 | cites it |
| 2025-02-14 | [Soybean futures responses to meteorological disaster risk —— Empirical evidence from the Chicago board of trade](https://doi.org/10.1016/j.frl.2025.106904) | [Finance research letters](https://scholar4ai.com/journals/finance-research-letters.md) | Yu Yang, Huilu Rong, Gaoxin Cheng et al. | 1 | cites it |
| 2025-06-04 | [The future of urban hierearchy and Zipf law: ARIMA and BATS forecasting](https://doi.org/10.1007/s12076-025-00408-z) | [Letters in Spatial and Resource Sciences](https://scholar4ai.com/journals/letters-in-spatial-and-resource-sciences.md) | Hasan Engìn Duran | 1 | cites it |
| 2025-12-24 | [A perceived quality quantification method for experiential products considering ambiguity, correlation, and dynamics of features](https://doi.org/10.1007/s10660-025-10035-x) | [Electronic Commerce Research](https://scholar4ai.com/journals/electronic-commerce-research.md) | Qianqian Chen, zhongjun tang, Duokui He et al. | 1 | cites it |
| 2022-02-22 | [Optimal pricing for electricity retailers based on data-driven consumers’ price-response](https://doi.org/10.1007/s11750-022-00622-8) | [Top](https://scholar4ai.com/journals/top.md) | Román Pérez-Santalla, Miguel Carrión, Carlos Ruiz | 0 | cites it |
| 2026-02-28 | [Is the financial market efficient? An advanced time series analysis](https://doi.org/10.1186/s40854-025-00856-y) | [Financial Innovation](https://scholar4ai.com/journals/financial-innovation.md) | Siqi Mao, Lin-Xi Meng, Adrian Barbu et al. | 0 | cites it |
| 2026-03-21 | [WaveESN–RegimeMLP: GA-Tuned Reservoirs and Regime-Aware Multiscale Forecasting](https://doi.org/10.1007/s10614-026-11343-6) | [Computational Economics](https://scholar4ai.com/journals/computational-economics.md) | Çağlar Sözen | 0 | cites it |
| 2026-04-21 | [Evaluating LSTM deep learning models for agricultural price forecasting: a case study on citrus markets in Corrientes, Argentina](https://doi.org/10.1007/s00521-026-11915-5) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Claudia Screpnik, Eduardo Zamudio, Laura Giménez | 0 | cites it |
| 2026-05-28 | [Prediction of stable GARCH time series using auxiliary processes](https://doi.org/10.1007/s00184-026-01034-5) | [Metrika](https://scholar4ai.com/journals/metrika.md) | Mohammad Mohammadi, W. Brent Lindquist | 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). fpp2 (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-fpp2

```bibtex
@misc{scholar4ai-code-cran-fpp2,
  author = {{Scholar4AI}},
  title = {fpp2 (R package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/cran-fpp2}},
  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/).