psvd
Eigendecomposition, Singular-Values and the Power Method
For a data matrix with m rows and n columns (m>=n), the power method is used to compute, simultaneously, the eigendecomposition of a square symmetric matrix. This result is used to obtain the singular value decomposition (SVD) and the principal component analysis (PCA) results. Compared to the classical SVD method, the first r singular values can be computed.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1-0 |
rolling linux/jammy R-4.5 | psvd_1.1-0.tar.gz |
32.2 KiB |
1.1-0 |
rolling linux/noble R-4.5 | psvd_1.1-0.tar.gz |
32.1 KiB |
1.1-0 |
rolling source/ R- | psvd_1.1-0.tar.gz |
6.1 KiB |
1.1-0 |
latest linux/jammy R-4.5 | psvd_1.1-0.tar.gz |
32.2 KiB |
1.1-0 |
latest linux/noble R-4.5 | psvd_1.1-0.tar.gz |
32.1 KiB |
1.1-0 |
latest source/ R- | psvd_1.1-0.tar.gz |
6.1 KiB |
1.1-0 |
2026-04-26 source/ R- | psvd_1.1-0.tar.gz |
6.1 KiB |
1.1-0 |
2026-04-23 source/ R- | psvd_1.1-0.tar.gz |
6.1 KiB |
1.1-0 |
2026-04-09 windows/windows R-4.5 | psvd_1.1-0.zip |
38.5 KiB |
0.1-0 |
2025-04-20 source/ R- | psvd_0.1-0.tar.gz |
6.0 KiB |