FADPclust
1.1.1Functional Data Clustering Using Adaptive Density Peak Detection
Overview
An implementation of a clustering algorithm for functional data based on adaptive density peak detection technique, in which the density is estimated by functional k-nearest neighbor density estimation based on a proposed semi-metric between functions. The proposed functional data clustering algorithm is computationally fast since it does not need iterative process. (Alex Rodriguez and Alessandro Laio (2014) doi:10.1126/science.1242072; Xiao-Feng Wang and Yifan Xu (2016) doi:10.1177/0962280215609948).
Install
Health
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- NOTE2026-06-090 OK · 13 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-080 OK · 12 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-03-100 OK · 14 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 33%
- References docs
- 20%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 1.1.1Latest
- 1.1.02022-11-04 · diff ↗
- RR 4.2.0 released · 2022-04-22
- 0.1.02021-10-08
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2021-10-08
- Total releases
- 3 / 5 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 63 KB / 2 files
- Download size
- 72 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("FADPclust")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
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