--- title: "fda (R package): papers citing this CRAN package" description: "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." url: https://scholar4ai.com/code/cran-fda markdown_url: https://scholar4ai.com/code/cran-fda.md license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/) share_text: "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. (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) --- # fda (R package): papers linking to it 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. - CRAN - https://CRAN.R-project.org/package=fda All repositories: https://scholar4ai.com/code.md ## 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 *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](https://scholar4ai.com/journals/computational-statistics.md) | 6 | | [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | 2 | | [Statistical Papers](https://scholar4ai.com/journals/statistical-papers.md) | 2 | | [Scientometrics](https://scholar4ai.com/journals/scientometrics.md) | 1 | | [Spatial Statistics](https://scholar4ai.com/journals/spatial-statistics.md) | 1 | ## Papers *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](https://doi.org/10.1007/s00180-018-0842-7) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Tomasz Górecki, Łukasz Smaga | 77 | cites it | | 2016-11-12 | [A statistical method for estimating predictable differences between daily traffic flow profiles](https://doi.org/10.1016/j.trb.2016.11.004) | [Transportation Research Part B Methodological](https://scholar4ai.com/journals/transportation-research-part-b-methodological.md) | 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](https://doi.org/10.1007/s00180-022-01259-8) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | 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](https://doi.org/10.1007/s10462-018-9666-7) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | Tomasz Górecki, Mirosław Krzyśko, Waldemar Wołyński | 27 | cites it | | 2023-03-09 | [Sparse and smooth functional data clustering](https://doi.org/10.1007/s00362-023-01408-1) | [Statistical Papers](https://scholar4ai.com/journals/statistical-papers.md) | Fabio Centofanti, Antonio Lepore, Biagio Palumbo | 19 | cites it | | 2021-09-09 | [Bayesian optimization of functional output in inverse problems](https://doi.org/10.1007/s11081-021-09677-1) | [Optimization and Engineering](https://scholar4ai.com/journals/optimization-and-engineering.md) | 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](https://doi.org/10.1007/s00180-021-01066-7) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Patricio Maturana‐Russel, Renate Meyer | 10 | cites it | | 2022-04-23 | [Selecting the derivative of a functional covariate in scalar-on-function regression](https://doi.org/10.1007/s11222-022-10091-5) | [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | Giles Hooker, Han Lin Shang | 5 | cites it | | 2023-12-01 | [Fourier approach to goodness-of-fit tests for Gaussian random processes](https://doi.org/10.1007/s00362-023-01510-4) | [Statistical Papers](https://scholar4ai.com/journals/statistical-papers.md) | 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](https://doi.org/10.1007/s11222-024-10455-z) | [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | 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](https://doi.org/10.1007/s11192-023-04722-5) | [Scientometrics](https://scholar4ai.com/journals/scientometrics.md) | Valentina Rizzoli, Matilde Trevisani, Arjuna Tuzzi | 4 | cites it | | 2025-06-25 | [Robust variable selection in high-dimensional nonparametric additive model](https://doi.org/10.1007/s10463-025-00939-8) | [Annals of the Institute of Statistical Mathematics](https://scholar4ai.com/journals/annals-of-the-institute-of-statistical-mathematics.md) | Suneel Babu Chatla, Abhijit Mandal | 3 | cites it | | 2017-06-23 | [Bootstrap based uncertainty bands for prediction in functional kriging](https://doi.org/10.1016/j.spasta.2017.06.005) | [Spatial Statistics](https://scholar4ai.com/journals/spatial-statistics.md) | Maria Franco‐Villoria, Rosaria Ignaccolo | 2 | cites it | | 2023-03-20 | [Unsupervised learning on U.S. weather forecast performance](https://doi.org/10.1007/s00180-023-01340-w) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | 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](https://doi.org/10.1007/s10994-023-06315-y) | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | 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](https://doi.org/10.1016/j.neunet.2025.108443) | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | 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](https://doi.org/10.1007/s00180-018-0819-6) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Jan Koláček, Ondřej Pokora, Daniela Kuruczová et al. | 1 | cites it | | 2024-03-02 | [Degree selection methods for curve estimation via Bernstein polynomials](https://doi.org/10.1007/s00180-024-01473-6) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | 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 ```bibtex @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} } ``` License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).