SPCAvRP
Sparse Principal Component Analysis via Random Projections (SPCAvRP)
Implements the SPCAvRP algorithm, developed and analysed in "Sparse principal component analysis via random projections" Gataric, M., Wang, T. and Samworth, R. J. (2018) <arXiv:1712.05630>. The algorithm is based on the aggregation of eigenvector information from carefully-selected random projections of the sample covariance matrix.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.4 |
rolling linux/jammy R-4.5 | SPCAvRP_0.4.tar.gz |
43.4 KiB |
0.4 |
rolling linux/noble R-4.5 | SPCAvRP_0.4.tar.gz |
43.2 KiB |
0.4 |
rolling source/ R- | SPCAvRP_0.4.tar.gz |
7.1 KiB |
0.4 |
latest linux/jammy R-4.5 | SPCAvRP_0.4.tar.gz |
43.4 KiB |
0.4 |
latest linux/noble R-4.5 | SPCAvRP_0.4.tar.gz |
43.2 KiB |
0.4 |
latest source/ R- | SPCAvRP_0.4.tar.gz |
7.1 KiB |
0.4 |
2026-04-26 source/ R- | SPCAvRP_0.4.tar.gz |
7.1 KiB |
0.4 |
2026-04-23 source/ R- | SPCAvRP_0.4.tar.gz |
7.1 KiB |
0.4 |
2026-04-09 windows/windows R-4.5 | SPCAvRP_0.4.zip |
45.9 KiB |
0.4 |
2025-04-20 source/ R- | SPCAvRP_0.4.tar.gz |
7.1 KiB |