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:Milana Gataric, Tengyao Wang and Richard J. Samworth

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'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 stars 8 scripts 139 downloads 3 exports 1 dependencies

Last updated 6 years agofrom:dcc6a99aca. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 02 2024
R-4.5-winOKNov 02 2024
R-4.5-linuxOKNov 02 2024
R-4.4-winOKNov 02 2024
R-4.4-macOKNov 02 2024
R-4.3-winOKNov 02 2024
R-4.3-macOKNov 02 2024

Exports:SPCAvRPSPCAvRP_deflationSPCAvRP_subspace

Dependencies:MASS