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:Doulaye Dembele [aut, cre]

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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'))

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 6 exports 0 dependencies

Last updated 29 days agofrom:5cb0c863b9. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 26 2024
R-4.5-win-x86_64OKOct 26 2024
R-4.5-linux-x86_64OKOct 26 2024
R-4.4-win-x86_64OKOct 26 2024
R-4.4-mac-x86_64OKOct 26 2024
R-4.4-mac-aarch64OKOct 26 2024
R-4.3-win-x86_64OKOct 26 2024
R-4.3-mac-x86_64OKOct 26 2024
R-4.3-mac-aarch64OKOct 26 2024

Exports:calcPCAcalcSVDeigenVeigenVcmGSmGSc

Dependencies: