rSDR
Robust Sufficient Dimension Reduction
A novel sufficient-dimension reduction method is robust against outliers using alpha-distance covariance and manifold-learning in dimensionality reduction problems. Please refer Hsin-Hsiung Huang, Feng Yu & Teng Zhang (2024) <doi:10.1080/10485252.2024.2313137> for the details.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.3.0 |
rolling linux/jammy R-4.5 | rSDR_1.0.3.0.tar.gz |
134.6 KiB |
1.0.3.0 |
rolling linux/noble R-4.5 | rSDR_1.0.3.0.tar.gz |
134.5 KiB |
1.0.3.0 |
rolling source/ R- | rSDR_1.0.3.0.tar.gz |
103.9 KiB |
1.0.3.0 |
latest linux/jammy R-4.5 | rSDR_1.0.3.0.tar.gz |
134.6 KiB |
1.0.3.0 |
latest linux/noble R-4.5 | rSDR_1.0.3.0.tar.gz |
134.5 KiB |
1.0.3.0 |
latest source/ R- | rSDR_1.0.3.0.tar.gz |
103.9 KiB |
1.0.3.0 |
2026-04-26 source/ R- | rSDR_1.0.3.0.tar.gz |
103.9 KiB |
1.0.3.0 |
2026-04-23 source/ R- | rSDR_1.0.3.0.tar.gz |
103.9 KiB |
1.0.3.0 |
2026-04-09 windows/windows R-4.5 | rSDR_1.0.3.0.zip |
138.0 KiB |