rsvddpd
Robust Singular Value Decomposition using Density Power Divergence
Computing singular value decomposition with robustness is a challenging task. This package provides an implementation of computing robust SVD using density power divergence (<doi:10.48550/arXiv.2109.10680>). It combines the idea of robustness and efficiency in estimation based on a tuning parameter. It also provides utility functions to simulate various scenarios to compare performances of different algorithms.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.1 |
rolling linux/jammy R-4.5 | rsvddpd_1.0.1.tar.gz |
113.9 KiB |
1.0.1 |
rolling linux/noble R-4.5 | rsvddpd_1.0.1.tar.gz |
117.0 KiB |
1.0.1 |
rolling source/ R- | rsvddpd_1.0.1.tar.gz |
32.4 KiB |
1.0.1 |
latest linux/jammy R-4.5 | rsvddpd_1.0.1.tar.gz |
113.9 KiB |
1.0.1 |
latest linux/noble R-4.5 | rsvddpd_1.0.1.tar.gz |
117.0 KiB |
1.0.1 |
latest source/ R- | rsvddpd_1.0.1.tar.gz |
32.4 KiB |
1.0.1 |
2026-04-26 source/ R- | rsvddpd_1.0.1.tar.gz |
32.4 KiB |
1.0.1 |
2026-04-23 source/ R- | rsvddpd_1.0.1.tar.gz |
32.4 KiB |
1.0.1 |
2026-04-09 windows/windows R-4.5 | rsvddpd_1.0.1.zip |
527.1 KiB |
1.0.0 |
2025-04-20 source/ R- | rsvddpd_1.0.0.tar.gz |
31.1 KiB |