Package: psvd 1.1-0
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_1.1-0.tar.gz
psvd_1.1-0.zip(r-4.7)psvd_1.1-0.zip(r-4.6)psvd_1.1-0.zip(r-4.5)
psvd_1.1-0.tgz(r-4.6-x86_64)psvd_1.1-0.tgz(r-4.6-arm64)psvd_1.1-0.tgz(r-4.5-x86_64)psvd_1.1-0.tgz(r-4.5-arm64)
psvd_1.1-0.tar.gz(r-4.7-arm64)psvd_1.1-0.tar.gz(r-4.7-x86_64)psvd_1.1-0.tar.gz(r-4.6-arm64)psvd_1.1-0.tar.gz(r-4.6-x86_64)
psvd_1.1-0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
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 from:bac75b8819. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 108 | ||
| linux-devel-x86_64 | OK | 96 | ||
| source / vignettes | OK | 135 | ||
| linux-release-arm64 | OK | 151 | ||
| linux-release-x86_64 | OK | 93 | ||
| macos-release-arm64 | OK | 125 | ||
| macos-release-x86_64 | OK | 225 | ||
| macos-oldrel-arm64 | OK | 130 | ||
| macos-oldrel-x86_64 | OK | 225 | ||
| windows-devel | OK | 80 | ||
| windows-release | OK | 69 | ||
| windows-oldrel | OK | 69 | ||
| wasm-release | OK | 95 |
Exports:calcPCAcalcSVDeigenVeigenVcmGSmGSc
Dependencies:
