fda (R package): papers linking to it

← Code and data repositories cited in research papers

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

18 papers in the tracked journals link to fda (R package) in their Crossref records, the first in 2016; most of them (5) in 2023.
By category: Statistics (12), AI (3) and Operations Research (2); the journals with the most are Computational Statistics (6), Statistics and Computing (2) and Statistical Papers (2).

By year#

20162025

Papers linking to fda (R package) by publication year
Year	Papers
2016	1
2017	1
2018	3
2021	2
2022	2
2023	5
2024	2
2025	2

Journals#

Journals whose papers link to fda (R package) most
Journal	Papers
Computational Statistics	6
Statistics and Computing	2
Statistical Papers	2
Scientometrics	1
Spatial Statistics	1

Papers linking to fda (R package), most cited first
Published	Title	Journal	Authors	Citations	Link
2018-09-27	fdANOVA: an R software package for analysis of variance for univariate and multivariate functional data	Computational Statistics	Tomasz Górecki, Łukasz Smaga	77	cites it
2016-11-12	A statistical method for estimating predictable differences between daily traffic flow profiles	Transportation Research Part B Methodological	Fiona Crawford, David Paul Watling, Richard Dominic Connors	69	cites it
2022-07-25	Combining unsupervised and supervised learning techniques for enhancing the performance of functional data classifiers	Computational Statistics	Fabrizio Maturo, Rosanna Verde	28	cites it
2018-11-10	Independence test and canonical correlation analysis based on the alignment between kernel matrices for multivariate functional data	Artificial Intelligence Review	Tomasz Górecki, Mirosław Krzyśko, Waldemar Wołyński	27	cites it
2023-03-09	Sparse and smooth functional data clustering	Statistical Papers	Fabio Centofanti, Antonio Lepore, Biagio Palumbo	19	cites it
2021-09-09	Bayesian optimization of functional output in inverse problems	Optimization and Engineering	Chaofan Huang, Yi Ren, Emily K. McGuinness et al.	18	cites it
2021-01-20	Bayesian spectral density estimation using P-splines with quantile-based knot placement	Computational Statistics	Patricio Maturana‐Russel, Renate Meyer	10	cites it
2022-04-23	Selecting the derivative of a functional covariate in scalar-on-function regression	Statistics and Computing	Giles Hooker, Han Lin Shang	5	cites it
2023-12-01	Fourier approach to goodness-of-fit tests for Gaussian random processes	Statistical Papers	Petr Čoupek, Viktor Dolník, Zdeněk Hlávka et al.	5	cites it
2024-07-11	A mixture of experts regression model for functional response with functional covariates	Statistics and Computing	Jean Steve TAMO TCHOMGUI, Julien Jacques, Guillaume Fraysse et al.	5	cites it
2023-05-18	Portraying the life cycle of ideas in social psychology through functional (textual) data analysis: a toolkit for digital history	Scientometrics	Valentina Rizzoli, Matilde Trevisani, Arjuna Tuzzi	4	cites it
2025-06-25	Robust variable selection in high-dimensional nonparametric additive model	Annals of the Institute of Statistical Mathematics	Suneel Babu Chatla, Abhijit Mandal	3	cites it
2017-06-23	Bootstrap based uncertainty bands for prediction in functional kriging	Spatial Statistics	Maria Franco‐Villoria, Rosaria Ignaccolo	2	cites it
2023-03-20	Unsupervised learning on U.S. weather forecast performance	Computational Statistics	Chuyuan Lin, Ying Yu, Lucas Y. Wu et al.	2	cites it
2023-04-24	Data driven discovery of systems of ordinary differential equations using nonconvex multitask learning	Machine Learning	Clément Lejeune, Josiane Mothe, Adil Soubki et al.	2	cites it
2025-12-09	2D Time-varying functional modeling framework for multi-scale solar irradiance forecasting	Neural Networks	Chengdong Shi, Wei Zhao, Xiao‐Jun Zeng et al.	2	cites it
2018-05-14	Benefits of functional PCA in the analysis of single-trial auditory evoked potentials	Computational Statistics	Jan Koláček, Ondřej Pokora, Daniela Kuruczová et al.	1	cites it
2024-03-02	Degree selection methods for curve estimation via Bernstein polynomials	Computational Statistics	Juliana Freitas de Mello e Silva, Sujit Kumar Ghosh, Vinícius Diniz Mayrink	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). fda (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-fda

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