Package: psvd 0.1-0
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.
Authors:
psvd_0.1-0.tar.gz
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psvd_0.1-0.tgz(r-4.4-x86_64)psvd_0.1-0.tgz(r-4.4-arm64)psvd_0.1-0.tgz(r-4.3-x86_64)psvd_0.1-0.tgz(r-4.3-arm64)
psvd_0.1-0.tar.gz(r-4.5-noble)psvd_0.1-0.tar.gz(r-4.4-noble)
psvd_0.1-0.tgz(r-4.4-emscripten)psvd_0.1-0.tgz(r-4.3-emscripten)
psvd.pdf |psvd.html✨
psvd/json (API)
| # Install 'psvd' in R: |
| install.packages('psvd', repos = c('https://doulaye.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 days agofrom:5cb0c863b9. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 26 2024 |
| R-4.5-win-x86_64 | OK | Oct 26 2024 |
| R-4.5-linux-x86_64 | OK | Oct 26 2024 |
| R-4.4-win-x86_64 | OK | Oct 26 2024 |
| R-4.4-mac-x86_64 | OK | Oct 26 2024 |
| R-4.4-mac-aarch64 | OK | Oct 26 2024 |
| R-4.3-win-x86_64 | OK | Oct 26 2024 |
| R-4.3-mac-x86_64 | OK | Oct 26 2024 |
| R-4.3-mac-aarch64 | OK | Oct 26 2024 |
Exports:calcPCAcalcSVDeigenVeigenVcmGSmGSc
Dependencies:
