RaJIVE
Robust Angle Based Joint and Individual Variation Explained
A robust alternative to the aJIVE (angle based Joint and Individual Variation Explained) method (Feng et al 2018: <doi:10.1016/j.jmva.2018.03.008>) for the estimation of joint and individual components in the presence of outliers in multi-source data. It decomposes the multi-source data into joint, individual and residual (noise) contributions. The decomposition is robust to outliers and noise in the data. The method is illustrated in Ponzi et al (2021) <arXiv:2101.09110>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0 |
rolling linux/jammy R-4.5 | RaJIVE_1.0.tar.gz |
214.8 KiB |
1.0 |
rolling linux/noble R-4.5 | RaJIVE_1.0.tar.gz |
214.9 KiB |
1.0 |
rolling source/ R- | RaJIVE_1.0.tar.gz |
155.5 KiB |
1.0 |
latest linux/jammy R-4.5 | RaJIVE_1.0.tar.gz |
214.8 KiB |
1.0 |
latest linux/noble R-4.5 | RaJIVE_1.0.tar.gz |
214.9 KiB |
1.0 |
latest source/ R- | RaJIVE_1.0.tar.gz |
155.5 KiB |
1.0 |
2026-04-26 source/ R- | RaJIVE_1.0.tar.gz |
155.5 KiB |
1.0 |
2026-04-23 source/ R- | RaJIVE_1.0.tar.gz |
155.5 KiB |
1.0 |
2026-04-09 windows/windows R-4.5 | RaJIVE_1.0.zip |
218.1 KiB |
1.0 |
2025-04-20 source/ R- | RaJIVE_1.0.tar.gz |
155.5 KiB |