KFPCA
Kendall Functional Principal Component Analysis
Implementation for Kendall functional principal component analysis. Kendall functional principal component analysis is a robust functional principal component analysis technique for non-Gaussian functional/longitudinal data. The crucial function of this package is KFPCA() and KFPCA_reg(). Moreover, least square estimates of functional principal component scores are also provided. Refer to Rou Zhong, Shishi Liu, Haocheng Li, Jingxiao Zhang. (2021) <arXiv:2102.01286>. Rou Zhong, Shishi Liu, Haocheng Li, Jingxiao Zhang. (2021) <doi:10.1016/j.jmva.2021.104864>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.0 |
rolling linux/jammy R-4.5 | KFPCA_2.0.tar.gz |
84.9 KiB |
2.0 |
rolling linux/noble R-4.5 | KFPCA_2.0.tar.gz |
84.5 KiB |
2.0 |
rolling source/ R- | KFPCA_2.0.tar.gz |
22.7 KiB |
2.0 |
latest linux/jammy R-4.5 | KFPCA_2.0.tar.gz |
84.9 KiB |
2.0 |
latest linux/noble R-4.5 | KFPCA_2.0.tar.gz |
84.5 KiB |
2.0 |
latest source/ R- | KFPCA_2.0.tar.gz |
22.7 KiB |
2.0 |
2026-04-26 source/ R- | KFPCA_2.0.tar.gz |
22.7 KiB |
2.0 |
2026-04-23 source/ R- | KFPCA_2.0.tar.gz |
22.7 KiB |
2.0 |
2026-04-09 windows/windows R-4.5 | KFPCA_2.0.zip |
87.7 KiB |
2.0 |
2025-04-20 source/ R- | KFPCA_2.0.tar.gz |
22.7 KiB |