bigstatsr: Statistical Tools for Filebacked Big Matrices

Easy-to-use, efficient, flexible and scalable statistical tools. Package bigstatsr provides and uses Filebacked Big Matrices via memory-mapping. It provides for instance matrix operations, Principal Component Analysis, sparse linear supervised models, utility functions and more. A scientific paper associated with this package is in preparation.

Version: 0.2.2
Depends: R (≥ 3.3.2)
Imports: cowplot, doParallel, foreach, ggplot2, glue, graphics, magrittr, Matrix, methods, parallel, Rcpp, RSpectra, stats
LinkingTo: BH, Rcpp, RcppArmadillo
Suggests: biglasso, bigmemory, covr, glmnet, grid, LiblineaR, sparseSVM, testthat, viridis
Published: 2017-09-02
Author: Florian Privé [aut, cre], Michael Blum [ths], Hugues Aschard [ths]
Maintainer: Florian Privé <florian.prive.21 at gmail.com>
BugReports: https://github.com/privefl/bigstatsr/issues
License: GPL-3
URL: https://privefl.github.io/bigstatsr
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: bigstatsr results

Downloads:

Reference manual: bigstatsr.pdf
Package source: bigstatsr_0.2.2.tar.gz
Windows binaries: r-devel: bigstatsr_0.2.2.zip, r-release: bigstatsr_0.2.2.zip, r-oldrel: bigstatsr_0.2.2.zip
OS X El Capitan binaries: r-release: bigstatsr_0.2.2.tgz
OS X Mavericks binaries: r-oldrel: bigstatsr_0.2.2.tgz
Old sources: bigstatsr archive

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