maxLik (R package): papers linking to it

CRAN · CRAN.R-project.org/package=maxLik

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to maxLik (R package) (https://CRAN.R-project.org/package=maxLik), 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 maxLik (R package) in their Crossref records, the first in 2022; most of them (2) in 2023.
By category: Operations Research (2) and Statistics (2); the journals with the most are Transportation Research Part A Policy and Practice (2) and Computational Statistics (2).
2 of the papers build on one another: a later paper cites an earlier one that also links maxLik (R package).

By year#

20222025

Papers linking to maxLik (R package) by publication year
Year	Papers
2022	1
2023	2
2025	1

Journals#

Journals whose papers link to maxLik (R package) most
Journal	Papers
Transportation Research Part A Policy and Practice	2
Computational Statistics	2

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.

Public preferences for distribution in the context of transport investments Transportation Research Part A Policy and Practice, 2022
- Do the distributional preferences of national infrastructure planners diverge from those of the public? Transportation Research Part A Policy and Practice, 2023 — cites the paper above

Papers linking to maxLik (R package), most cited first
Published	Title	Journal	Authors	Citations	Link
2022-02-03	Public preferences for distribution in the context of transport investments	Transportation Research Part A Policy and Practice	Anders Bondemark, Henrik Andersson, Karin Brundell-Freij	7	cites it
2023-03-01	Do the distributional preferences of national infrastructure planners diverge from those of the public?	Transportation Research Part A Policy and Practice	Anders Bondemark, Henrik Andersson, Karin Brundell-Freij	2	cites it
2023-05-02	An expectation conditional maximization algorithm for the skew-normal based stochastic frontier model	Computational Statistics	Xiaonan Zhu, Zheng Mao Wei, Tonghui Wang et al.	2	cites it
2025-05-28	Maximum likelihood estimation of parameters for double poisson regression: a simulation study	Computational Statistics	Sebastian Appelbaum, Thomas Ostermann, Uwe Konerding	2	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). maxLik (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-maxlik

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