---
title: "fda.usc (R package): papers citing this CRAN package"
description: "4 papers in the tracked journals link to fda.usc (R package) in their Crossref records, the first in 2019; most of them (2) in 2019."
url: https://scholar4ai.com/code/cran-fda-usc
markdown_url: https://scholar4ai.com/code/cran-fda-usc.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "4 papers in the tracked journals link to fda.usc (R package) in their Crossref records, the first in 2019; most of them (2) in 2019. (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.usc (R package): papers linking to it

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

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

## Key findings

- 4 papers in the tracked journals link to fda.usc (R package) in their Crossref records, the first in 2019; most of them (2) in 2019.
- By category: Statistics (3) and AI (1); the journals with the most are Computational Statistics (1), Neural Networks (1) and Journal of Multivariate Analysis (1).
- 2 of the papers build on one another: a later paper cites an earlier one that also links fda.usc (R package).

## By year

*Papers linking to fda.usc (R package) by publication year*

| Year | Papers |
|---|---:|
| 2019 | 2 |
| 2020 | 1 |
| 2025 | 1 |

## Journals

*Journals whose papers link to fda.usc (R package) most*

| Journal | Papers |
|---|---:|
| [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | 1 |
| [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | 1 |
| [Journal of Multivariate Analysis](https://scholar4ai.com/journals/journal-of-multivariate-analysis.md) | 1 |
| [Statistical Papers](https://scholar4ai.com/journals/statistical-papers.md) | 1 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [Wild bootstrap bandwidth selection of recursive nonparametric relative regression for independent functional data](https://doi.org/10.1016/j.jmva.2019.04.009) (Journal of Multivariate Analysis, 2019)
  - [Recursive non-parametric kernel classification rule estimation for independent functional data](https://doi.org/10.1007/s00180-020-01024-9) (Computational Statistics, 2020) — cites the paper above

## Papers

*Papers linking to fda.usc (R package), most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2019-05-17 | [Wild bootstrap bandwidth selection of recursive nonparametric relative regression for independent functional data](https://doi.org/10.1016/j.jmva.2019.04.009) | [Journal of Multivariate Analysis](https://scholar4ai.com/journals/journal-of-multivariate-analysis.md) | Yousri Slaoui | 20 | cites it |
| 2019-01-01 | [FPCA-based estimation for generalized functional partially linear models](https://doi.org/10.1007/s00362-018-01066-8) | [Statistical Papers](https://scholar4ai.com/journals/statistical-papers.md) | Ruiyuan Cao, Jiang Du, Jianjun Zhou et al. | 14 | 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 |
| 2020-08-18 | [Recursive non-parametric kernel classification rule estimation for independent functional data](https://doi.org/10.1007/s00180-020-01024-9) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Yousri Slaoui | 1 | 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.usc (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-fda-usc

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