wideRhino
High-Dimensional Methods via Generalised Singular Decomposition
Construct a Canonical Variate Analysis Biplot via the Generalised Singular Value Decomposition, for cases when the number of samples is less than the number of variables. For more information on biplots, see Gower JC, Lubbe SG, Le Roux NJ (2011) <doi:10.1002/9780470973196> and for more information on the generalised singular value decomposition, see Edelman A, Wang Y (2020) <doi:10.1137/18M1234412>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.2 |
rolling linux/jammy R-4.5 | wideRhino_1.0.2.tar.gz |
1.3 MiB |
1.0.2 |
rolling linux/noble R-4.5 | wideRhino_1.0.2.tar.gz |
1.3 MiB |
1.0.2 |
rolling source/ R- | wideRhino_1.0.2.tar.gz |
1.3 MiB |
1.0.2 |
latest linux/jammy R-4.5 | wideRhino_1.0.2.tar.gz |
1.3 MiB |
1.0.2 |
latest linux/noble R-4.5 | wideRhino_1.0.2.tar.gz |
1.3 MiB |
1.0.2 |
latest source/ R- | wideRhino_1.0.2.tar.gz |
1.3 MiB |
1.0.2 |
2026-04-26 source/ R- | wideRhino_1.0.2.tar.gz |
1.3 MiB |
1.0.2 |
2026-04-23 source/ R- | wideRhino_1.0.2.tar.gz |
1.3 MiB |
1.0.2 |
2026-04-09 windows/windows R-4.5 | wideRhino_1.0.2.zip |
1.3 MiB |