bdsvd
Block Structure Detection Using Singular Vectors
Provides methods to perform block diagonal covariance matrix detection using singular vectors ('BD-SVD'), which can be extended to inherently sparse principal component analysis ('IS-PCA'). The methods are described in Bauer (2025) <doi:10.1080/10618600.2024.2422985> and Bauer (2026) <doi:10.48550/arXiv.2510.03729>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.2.1 |
rolling linux/jammy R-4.5 | bdsvd_1.2.1.tar.gz |
134.4 KiB |
1.2.1 |
rolling linux/noble R-4.5 | bdsvd_1.2.1.tar.gz |
136.7 KiB |
1.2.1 |
rolling source/ R- | bdsvd_1.2.1.tar.gz |
20.8 KiB |
1.2.1 |
latest linux/jammy R-4.5 | bdsvd_1.2.1.tar.gz |
134.4 KiB |
1.2.1 |
latest linux/noble R-4.5 | bdsvd_1.2.1.tar.gz |
136.7 KiB |
1.2.1 |
latest source/ R- | bdsvd_1.2.1.tar.gz |
20.8 KiB |
1.2.1 |
2026-04-26 source/ R- | bdsvd_1.2.1.tar.gz |
20.8 KiB |
1.2.1 |
2026-04-23 source/ R- | bdsvd_1.2.1.tar.gz |
20.8 KiB |
1.2.1 |
2026-04-09 windows/windows R-4.5 | bdsvd_1.2.1.zip |
456.0 KiB |
0.2.1 |
2025-04-20 source/ R- | bdsvd_0.2.1.tar.gz |
14.6 KiB |