Package: irlba 2.3.7

irlba: Fast Truncated Singular Value Decomposition and Principal Components Analysis for Large Dense and Sparse Matrices

Fast and memory efficient methods for truncated singular value decomposition and principal components analysis of large sparse and dense matrices.

Authors:Jim Baglama [aut, cph], Lothar Reichel [aut, cph], B. W. Lewis [aut, cre, cph]

irlba_2.3.7.tar.gz
irlba_2.3.7.zip(r-4.7)irlba_2.3.7.zip(r-4.6)irlba_2.3.7.zip(r-4.5)
irlba_2.3.7.tgz(r-4.6-x86_64)irlba_2.3.7.tgz(r-4.6-arm64)irlba_2.3.7.tgz(r-4.5-x86_64)irlba_2.3.7.tgz(r-4.5-arm64)
irlba_2.3.7.tar.gz(r-4.7-arm64)irlba_2.3.7.tar.gz(r-4.7-x86_64)irlba_2.3.7.tar.gz(r-4.6-arm64)irlba_2.3.7.tar.gz(r-4.6-x86_64)
irlba_2.3.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
irlba/json (API)

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

Bug tracker:https://github.com/bwlewis/irlba/issues

Uses libs:
  • openblas– Optimized BLAS

On CRAN:

Conda:

pcaprincipal-component-analysissingular-value-decompositionsparse-principal-componentssvdopenblas

14.06 score 136 stars 357 packages 2.0k scripts 81k downloads 16 mentions 5 exports 2 dependencies

Last updated from:d22475deff. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK127
linux-devel-x86_64OK107
source / vignettesOK248
linux-release-arm64OK135
linux-release-x86_64OK118
macos-release-arm64OK164
macos-release-x86_64OK237
macos-oldrel-arm64OK137
macos-oldrel-x86_64OK246
windows-develOK152
windows-releaseOK134
windows-oldrelOK135
wasm-releaseOK93

Exports:irlbapartial_eigenprcomp_irlbassvdsvdr

Dependencies:latticeMatrix

irlba Manual

Rendered fromirlba.Rnwusingutils::Sweaveon May 27 2026.

Last update: 2017-10-05
Started: 2015-08-01