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.

Version: 2.3.2
Depends: Matrix
Imports: stats, methods
LinkingTo: Matrix
Suggests: PMA
Published: 2018-01-11
Author: Jim Baglama [aut, cph], Lothar Reichel [aut, cph], B. W. Lewis [aut, cre, cph]
Maintainer: B. W. Lewis <blewis at>
License: GPL-3
NeedsCompilation: yes
Materials: README
In views: NumericalMathematics
CRAN checks: irlba results


Reference manual: irlba.pdf
Vignettes: irlba Manual
Package source: irlba_2.3.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: irlba_2.3.2.tgz
OS X Mavericks binaries: r-oldrel: irlba_2.3.1.tgz
Old sources: irlba archive

Reverse dependencies:

Reverse depends: DDRTree, s4vd, semisupKernelPCA
Reverse imports: bigpca, denoiseR, fuser, gyriq, lolR, OmicKriging, randnet, recommenderlab, Seurat, text2vec
Reverse suggests: DrImpute, steadyICA, widyr


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