irlba: Fast partial SVD by implicitly-restarted Lanczos bidiagonalization

A fast and memory-efficient method for computing a few approximate singular values and singular vectors of large matrices.

Version: 1.0.3
Depends: R (≥ 2.15.0)
Imports: Matrix
Published: 2014-01-25
Author: Jim Baglama and Lothar Reichel
Maintainer: Bryan W. Lewis <blewis at>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
Materials: NEWS
In views: NumericalMathematics
CRAN checks: irlba results


Reference manual: irlba.pdf
Vignettes: irlba Manual
Package source: irlba_1.0.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: irlba_1.0.3.tgz, r-oldrel: irlba_1.0.3.tgz
OS X Mavericks binaries: r-release: irlba_1.0.3.tgz
Old sources: irlba archive

Reverse dependencies:

Reverse depends: clustrd, semisupKernelPCA
Reverse imports: bigpca, igraph, OmicKriging