opera (R package): papers linking to it

← Code and data repositories cited in research papers

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

Key findings#

4 papers in the tracked journals link to opera (R package) in their Crossref records, the first in 2018; most of them (2) in 2023.
By category: AI (3) and Statistics (1); the journals with the most are Machine Learning (2), Expert Systems with Applications (1) and Statistical Papers (1).
2 of the papers build on one another: a later paper cites an earlier one that also links opera (R package).

By year#

20182023

Papers linking to opera (R package) by publication year
Year	Papers
2018	1
2022	1
2023	2

Journals#

Journals whose papers link to opera (R package) most
Journal	Papers
Machine Learning	2
Expert Systems with Applications	1
Statistical Papers	1

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Arbitrage of forecasting experts Machine Learning, 2018
- Explainable online ensemble of deep neural network pruning for time series forecasting Machine Learning, 2022 — cites the paper above

Papers linking to opera (R package), most cited first
Published	Title	Journal	Authors	Citations	Link
2018-12-04	Arbitrage of forecasting experts	Machine Learning	Vítor Cerqueira, Luı́s Torgo, Fábio Pinto et al.	51	cites it
2022-08-02	Explainable online ensemble of deep neural network pruning for time series forecasting	Machine Learning	Amal Saadallah, Matthias Jakobs, Katharina J. Morik	19	cites it
2023-09-18	An algorithm for automatic selection and combination of forecast models	Expert Systems with Applications	Carlos García-Aroca, María Asunción Martínez Mayoral, Javier Morales et al.	8	cites it
2023-03-16	Kalman recursions Aggregated Online	Statistical Papers	Eric Adjakossa, Yannig Goude, Olivier Wintenberger	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). opera (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-opera

@misc{scholar4ai-code-cran-opera,
  author = {{Scholar4AI}},
  title = {opera (R package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/cran-opera}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

Free to reuse for non-commercial purposes with attribution (CC BY-NC 4.0).