---
title: "fdapace (R package): papers citing this CRAN package"
description: "5 papers in the tracked journals link to fdapace (R package) in their Crossref records, the first in 2020; most of them (2) in 2023."
url: https://scholar4ai.com/code/cran-fdapace
markdown_url: https://scholar4ai.com/code/cran-fdapace.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "5 papers in the tracked journals link to fdapace (R package) in their Crossref records, the first in 2020; most of them (2) 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)
---

# fdapace (R package): papers linking to it

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

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

## Key findings

- 5 papers in the tracked journals link to fdapace (R package) in their Crossref records, the first in 2020; most of them (2) in 2023.
- By category: Statistics (3), AI (1) and Economics (1); the journals with the most are Computational Statistics (1), Information Processing & Management (1) and Journal of Econometrics (1).

## By year

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

| Year | Papers |
|---|---:|
| 2020 | 1 |
| 2023 | 2 |
| 2025 | 1 |
| 2026 | 1 |

## Journals

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

| Journal | Papers |
|---|---:|
| [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | 1 |
| [Information Processing & Management](https://scholar4ai.com/journals/information-processing-management.md) | 1 |
| [Journal of Econometrics](https://scholar4ai.com/journals/journal-of-econometrics.md) | 1 |
| [Computational Statistics & Data Analysis](https://scholar4ai.com/journals/computational-statistics-data-analysis.md) | 1 |
| [Metrika](https://scholar4ai.com/journals/metrika.md) | 1 |

## Papers

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

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2020-06-09 | [Efficient Estimation for Varying-Coefficient Mixed Effects Models with Functional Response Data](https://doi.org/10.1007/s00184-020-00776-0) | [Metrika](https://scholar4ai.com/journals/metrika.md) | Xiong Cai, Liugen Xue, Xiaolong Pu et al. | 6 | cites it |
| 2023-11-04 | [Dynamic modeling for multivariate functional and longitudinal data](https://doi.org/10.1016/j.jeconom.2023.105573) | [Journal of Econometrics](https://scholar4ai.com/journals/journal-of-econometrics.md) | Siteng Hao, Shu‐Chin Lin, Jane-Ling Wang et al. | 5 | cites it |
| 2023-05-22 | [Tree-based boosting with functional data](https://doi.org/10.1007/s00180-023-01364-2) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Xiaomeng Ju, Matías Salibián‐Barrera | 1 | cites it |
| 2026-02-06 | [Functional data clustering and outlier identification via subgroup analysis with minimum spanning tree](https://doi.org/10.1016/j.ipm.2026.104646) | [Information Processing & Management](https://scholar4ai.com/journals/information-processing-management.md) | Chao Liu, Shimin Lin, Jiaqi Li | 1 | cites it |
| 2025-09-08 | [Measure selection for functional linear model](https://doi.org/10.1016/j.csda.2025.108270) | [Computational Statistics & Data Analysis](https://scholar4ai.com/journals/computational-statistics-data-analysis.md) | Su I Iao, Hans-Georg Müller | 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). fdapace (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-fdapace

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