bigpca: PCA, Transpose and Multicore Functionality for 'big.matrix' Objects

Adds wrappers to add functionality for big.matrix objects (see the bigmemory project). This allows fast scalable principle components analysis (PCA), or singular value decomposition (SVD). There are also functions for transposing, using multicore 'apply' functionality, data importing and for compact display of big.matrix objects. Most functions also work for standard matrices if RAM is sufficient.

Version: 1.1
Depends: R (≥ 3.0), grDevices, graphics, stats, utils, reader (≥ 1.0.1), NCmisc (≥ 1.1), bigmemory (≥ 4.0.0), biganalytics
Imports: parallel, methods, bigmemory.sri, irlba
Published: 2017-11-21
Author: Nicholas Cooper
Maintainer: Nicholas Cooper <njcooper at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: bigpca results


Reference manual: bigpca.pdf
Package source: bigpca_1.1.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel:
OS X binaries: r-release: bigpca_1.1.tgz, r-oldrel: bigpca_1.1.tgz
Old sources: bigpca archive


Please use the canonical form to link to this page.