apca
Advanced Principal Component Analysis
Provides nine computational algorithms for dimensionality reduction via Principal Component Analysis (PCA), built using an object-oriented (S3) architecture. The package includes classical and modern methods: Singular Value Decomposition (SVD) based on Eckart and Young (1936) <doi:10.1007/BF02288367>, Power Iteration based on Hotelling (1933) <doi:10.1037/h0071325>, QR Algorithm based on Francis (1961) <doi:10.1093/comjnl/4.3.265>, Jacobi Algorithm based on Jacobi (1846) <doi:10.1515/crll.1846.30.51>, Arnoldi Iteration based on Arnoldi (1951) <doi:10.1090/qam/42792>, 'NIPALS' based on Wold (1975) <doi:10.1017/S0021900200047604>, Alternating Least Squares (ALS) based on Kolda and Bader (2009) <doi:10.1137/07070111X>, Probabilistic PCA (PPCA) with EM Algorithm based on Tipping and Bishop (1999) <doi:10.1111/1467-9868.00196>, and Generalized Hebbian Algorithm (GHA) based on Sanger (1989) <doi:10.1016/0893-6080(89)90044-0>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | apca_1.0.0.tar.gz |
39.7 KiB |
1.0.0 |
rolling linux/noble R-4.5 | apca_1.0.0.tar.gz |
39.7 KiB |
1.0.0 |
rolling source/ R- | apca_1.0.0.tar.gz |
8.8 KiB |
1.0.0 |
latest linux/jammy R-4.5 | apca_1.0.0.tar.gz |
39.7 KiB |
1.0.0 |
latest linux/noble R-4.5 | apca_1.0.0.tar.gz |
39.7 KiB |
1.0.0 |
latest source/ R- | apca_1.0.0.tar.gz |
8.8 KiB |
1.0.0 |
2026-04-23 source/ R- | apca_1.0.0.tar.gz |
0 B |