---
title: "microbenchmark (R package): papers citing it"
description: "10 papers in the tracked journals link to microbenchmark (R package) in their Crossref records, the first in 2017; most of them (2) in 2025."
url: https://scholar4ai.com/code/cran-microbenchmark
markdown_url: https://scholar4ai.com/code/cran-microbenchmark.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "10 papers in the tracked journals link to microbenchmark (R package) in their Crossref records, the first in 2017; most of them (2) in 2025. (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)
---

# microbenchmark (R package): papers linking to it

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

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

## Key findings

- 10 papers in the tracked journals link to microbenchmark (R package) in their Crossref records, the first in 2017; most of them (2) in 2025.
- By category: Statistics (7), AI (2) and Economics (1); the journals with the most are Computational Statistics (4), Japanese Journal of Statistics and Data Science (1) and Applied Intelligence (1).

## By year

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

| Year | Papers |
|---|---:|
| 2017 | 2 |
| 2018 | 1 |
| 2019 | 1 |
| 2021 | 1 |
| 2022 | 1 |
| 2023 | 2 |
| 2025 | 2 |

## Journals

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

| Journal | Papers |
|---|---:|
| [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | 4 |
| [Japanese Journal of Statistics and Data Science](https://scholar4ai.com/journals/japanese-journal-of-statistics-and-data-science.md) | 1 |
| [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 1 |
| [Journal of Economic Dynamics and Control](https://scholar4ai.com/journals/journal-of-economic-dynamics-and-control.md) | 1 |
| [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | 1 |

## Papers

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

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2018-12-27 | [Inducing non-orthogonal and non-linear decision boundaries in decision trees via interactive basis functions](https://doi.org/10.1016/j.eswa.2018.12.041) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Antonio Páez, Fernando A. López Hernández, Manuel Ruiz Marín et al. | 20 | cites it |
| 2017-09-13 | [A survival ensemble of extreme learning machine](https://doi.org/10.1007/s10489-017-1063-4) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Hong Wang, Jianxin Wang, Lifeng Zhou | 14 | cites it |
| 2022-08-10 | [Copula shrinkage and portfolio allocation in ultra-high dimensions](https://doi.org/10.1016/j.jedc.2022.104508) | [Journal of Economic Dynamics and Control](https://scholar4ai.com/journals/journal-of-economic-dynamics-and-control.md) | Stanislav Anatolyev, Пырлик Владимир Николаевич | 6 | cites it |
| 2017-11-23 | [A least squares approach to latent variables extraction in formative–reflective models](https://doi.org/10.1016/j.csda.2017.11.006) | [Computational Statistics & Data Analysis](https://scholar4ai.com/journals/computational-statistics-data-analysis.md) | Marco Fattore, Matteo Maria Pelagatti, Giorgio Vittadini | 3 | cites it |
| 2019-06-12 | [Computing expectations and marginal likelihoods for permutations](https://doi.org/10.1007/s00180-019-00901-2) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Ben Powell, Paul A. Smith | 3 | cites it |
| 2023-06-10 | [Fast and consistent algorithm for the latent block model](https://doi.org/10.1007/s00180-023-01373-1) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Vincent Brault, Antoine Channarond | 3 | cites it |
| 2023-07-01 | [hermiter: R package for sequential nonparametric estimation](https://doi.org/10.1007/s00180-023-01382-0) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Michael Stephanou, Melvin Varughese | 1 | cites it |
| 2025-03-15 | [Estimation and model selection for finite mixtures of Tukey’s g- &-h distributions](https://doi.org/10.1007/s11222-025-10596-9) | [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | Tingting Zhan, Misung Yi, Amy R. Peck et al. | 1 | cites it |
| 2021-08-05 | [Computing highest density regions for continuous univariate distributions with known probability functions](https://doi.org/10.1007/s00180-021-01133-z) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Ben O’Neill | 0 | cites it |
| 2025-02-01 | [Fitting cure models using pseudo-observations approaches with the R package pseudoCure](https://doi.org/10.1007/s42081-024-00288-5) | [Japanese Journal of Statistics and Data Science](https://scholar4ai.com/journals/japanese-journal-of-statistics-and-data-science.md) | Sy Han Chiou, Chien‐Lin Su, Feng‐Chang Lin | 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). microbenchmark (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-microbenchmark

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