---
title: "Rmpfr (R package): papers citing this CRAN package"
description: "6 papers in the tracked journals link to Rmpfr (R package) in their Crossref records, the first in 2017; most of them (2) in 2017."
url: https://scholar4ai.com/code/cran-rmpfr
markdown_url: https://scholar4ai.com/code/cran-rmpfr.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "6 papers in the tracked journals link to Rmpfr (R package) in their Crossref records, the first in 2017; most of them (2) in 2017. (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)
---

# Rmpfr (R package): papers linking to it

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

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

## Key findings

- 6 papers in the tracked journals link to Rmpfr (R package) in their Crossref records, the first in 2017; most of them (2) in 2017.
- By category: Operations Research (3) and Statistics (3); the journals with the most are Methodology And Computing In Applied Probability (2), Computational Statistics (2) and European Journal of Operational Research (1).

## By year

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

| Year | Papers |
|---|---:|
| 2017 | 2 |
| 2018 | 1 |
| 2023 | 1 |
| 2024 | 1 |
| 2026 | 1 |

## Journals

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

| Journal | Papers |
|---|---:|
| [Methodology And Computing In Applied Probability](https://scholar4ai.com/journals/methodology-and-computing-in-applied-probability.md) | 2 |
| [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | 2 |
| [European Journal of Operational Research](https://scholar4ai.com/journals/european-journal-of-operational-research.md) | 1 |
| [Lifetime Data Analysis](https://scholar4ai.com/journals/lifetime-data-analysis.md) | 1 |

## Papers

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

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2017-12-05 | [Deep learning with long short-term memory networks for financial market predictions](https://doi.org/10.1016/j.ejor.2017.11.054) | [European Journal of Operational Research](https://scholar4ai.com/journals/european-journal-of-operational-research.md) | Thomas Günter Fischer, Christopher Krauß | 2,828 | cites it |
| 2017-03-27 | [Exponentiated Weibull regression for time-to-event data](https://doi.org/10.1007/s10985-017-9394-3) | [Lifetime Data Analysis](https://scholar4ai.com/journals/lifetime-data-analysis.md) | Shahedul A. Khan | 38 | cites it |
| 2018-07-16 | [Linear Combination of Independent Exponential Random Variables](https://doi.org/10.1007/s11009-018-9653-0) | [Methodology And Computing In Applied Probability](https://scholar4ai.com/journals/methodology-and-computing-in-applied-probability.md) | Kim-Hung Li, Cheuk Ting Li | 9 | cites it |
| 2023-05-15 | [Variational Bayes estimation of hierarchical Dirichlet-multinomial mixtures for text clustering](https://doi.org/10.1007/s00180-023-01350-8) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Massimo Bilancia, Michele Di Nanni, Fabio Manca et al. | 8 | cites it |
| 2024-04-10 | [A simple algorithm for computing the probabilities of count models based on pure birth processes](https://doi.org/10.1007/s00180-024-01491-4) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Mongkol Hunkrajok, Wanrudee Skulpakdee | 0 | cites it |
| 2026-09-01 | [Turing–Entropic Tail Classification: A Nonparametric Approach to Tail Inference](https://doi.org/10.1007/s11009-026-10320-8) | [Methodology And Computing In Applied Probability](https://scholar4ai.com/journals/methodology-and-computing-in-applied-probability.md) | Jialin Zhang, Zhiyi Zhang | 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). Rmpfr (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-rmpfr

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