Package: SPCAvRP 0.4
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.
Authors:
SPCAvRP_0.4.tar.gz
SPCAvRP_0.4.zip(r-4.5)SPCAvRP_0.4.zip(r-4.4)SPCAvRP_0.4.zip(r-4.3)
SPCAvRP_0.4.tgz(r-4.4-any)SPCAvRP_0.4.tgz(r-4.3-any)
SPCAvRP_0.4.tar.gz(r-4.5-noble)SPCAvRP_0.4.tar.gz(r-4.4-noble)
SPCAvRP_0.4.tgz(r-4.4-emscripten)SPCAvRP_0.4.tgz(r-4.3-emscripten)
SPCAvRP.pdf |SPCAvRP.html✨
SPCAvRP/json (API)
| # Install 'SPCAvRP' in R: |
| install.packages('SPCAvRP', repos = c('https://milanagataric.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:dcc6a99aca. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 03 2024 |
| R-4.5-win | OK | Sep 03 2024 |
| R-4.5-linux | OK | Sep 03 2024 |
| R-4.4-win | OK | Sep 03 2024 |
| R-4.4-mac | OK | Sep 03 2024 |
| R-4.3-win | OK | Sep 03 2024 |
| R-4.3-mac | OK | Sep 03 2024 |
Exports:SPCAvRPSPCAvRP_deflationSPCAvRP_subspace
Dependencies:MASS
