FADPclust
Functional Data Clustering Using Adaptive Density Peak Detection
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>).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1.1 |
rolling source/ R- | FADPclust_1.1.1.tar.gz |
71.7 KiB |
1.1.1 |
latest source/ R- | FADPclust_1.1.1.tar.gz |
71.7 KiB |
1.1.1 |
2026-04-23 source/ R- | FADPclust_1.1.1.tar.gz |
71.7 KiB |
1.1.1 |
2026-04-09 windows/windows R-4.5 | FADPclust_1.1.1.zip |
109.4 KiB |