Package: bdsvd 1.2.1

bdsvd: Block Structure Detection Using Singular Vectors

Provides methods to perform block diagonal covariance matrix detection using singular vectors ('BD-SVD'), which can be extended to inherently sparse principal component analysis ('IS-PCA'). The methods are described in Bauer (2025) <doi:10.1080/10618600.2024.2422985> and Bauer (2026) <doi:10.48550/arXiv.2510.03729>.

Authors:Jan O. Bauer [aut, cre], Ron Holzapfel [aut]

bdsvd_1.2.1.tar.gz
bdsvd_1.2.1.zip(r-4.7)bdsvd_1.2.1.zip(r-4.6)bdsvd_1.2.1.zip(r-4.5)
bdsvd_1.2.1.tgz(r-4.6-x86_64)bdsvd_1.2.1.tgz(r-4.6-arm64)bdsvd_1.2.1.tgz(r-4.5-x86_64)bdsvd_1.2.1.tgz(r-4.5-arm64)
bdsvd_1.2.1.tar.gz(r-4.7-arm64)bdsvd_1.2.1.tar.gz(r-4.7-x86_64)bdsvd_1.2.1.tar.gz(r-4.6-arm64)bdsvd_1.2.1.tar.gz(r-4.6-x86_64)
bdsvd_1.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
bdsvd/json (API)

# Install 'bdsvd' in R:
install.packages('bdsvd', repos = c('https://janobauer.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/janobauer/bdsvd/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

2.70 score 1 stars 508 downloads 9 exports 6 dependencies

Last updated from:99f4f65d45. Checks:11 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE150
linux-devel-x86_64NOTE158
source / vignettesOK200
linux-release-arm64NOTE148
linux-release-x86_64NOTE154
macos-release-arm64NOTE100
macos-release-x86_64NOTE226
macos-oldrel-arm64NOTE125
macos-oldrel-x86_64NOTE199
windows-develNOTE158
windows-releaseNOTE184
windows-oldrelNOTE169
wasm-releaseOK127

Exports:bdsvdbdsvd.cov.simbdsvd.htbdsvd.structurecdm.pcadetect.blocksispcaprmatssingle.bdsvd

Dependencies:irlbalatticeMatrixmatrixStatsRcppRcppArmadillo