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.

Install the latest version of this package by entering the following in R:
install.packages("bigpca")
AuthorNicholas Cooper
Date of publication2015-11-08 08:40:28
MaintainerNicholas Cooper <nick.cooper@cimr.cam.ac.uk>
LicenseGPL (>= 2)
Version1.0.3

View on CRAN

Functions

big.algebra.install.help Man page
bigpca Man page
big.PCA Man page
bigpca-package Man page
big.select Man page
big.t Man page
bmcapply Man page
check.text.matrix.format Man page
choose.comb.fn Man page
cut.fac Man page
dir.force.slash Man page
estimate.eig.vpcs Man page
generate.test.matrix Man page
get.big.matrix Man page
import.big.data Man page
manage.test.files Man page
matmul Man page
pca.scree.plot Man page
PC.correct Man page
PC.fn Man page
PC.fn.2 Man page
PC.fn.2.previous Man page
PC.fn.mat Man page
PC.fn.mat.apply Man page
PC.fn.mat.multi Man page
PC.fn.previous Man page
prv.big.matrix Man page
quick.elbow Man page
quick.mat.format Man page
quick.pheno.assocs Man page
row.rep Man page
select.col.row.custom Man page
select.least.assoc Man page
subcor.select Man page
subpc.select Man page
svn.bigalgebra.install Man page
thin Man page
uniform.select Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.