Encoding: UTF-8
Package: bigstatsr
Type: Package
Title: Statistical Tools for Filebacked Big Matrices
Version: 0.2.1
Date: 2017-08-30
Authors@R: c(
  person("Florian", "Privé", 
         email = "florian.prive.21@gmail.com", 
         role = c("aut", "cre")),
  person("Michael", "Blum", 
         email = "michael.blum@univ-grenoble-alpes.fr", 
         role = "ths"),
  person("Hugues", "Aschard", 
         email = "hugues.aschard@pasteur.fr",
         role = "ths"))
Description: 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.
License: GPL-3
LazyData: TRUE
ByteCompile: TRUE
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
RoxygenNote: 6.0.1
URL: https://privefl.github.io/bigstatsr
BugReports: https://github.com/privefl/bigstatsr/issues
Collate: 'AUC.R' 'CMSA.R' 'FBM-attach.R' 'crochet.R' 'FBM.R'
        'FBM-code256.R' 'FBM-copy.R' 'RcppExports.R' 'SVD.R'
        'apply-parallelize.R' 'biglasso.R' 'bigstatsr.R' 'colstats.R'
        'counts.R' 'crossprodSelf.R' 'plot.R' 'predict.R' 'randomSVD.R'
        'read.R' 'scaling.R' 'sparseSVM.R' 'tcrossprodSelf.R'
        'transpose.R' 'univLinReg.R' 'univLogReg.R' 'utils-assert.R'
        'utils-mult.R' 'utils.R' 'zzz.R'
NeedsCompilation: yes
Packaged: 2017-09-01 17:55:19 UTC; privef
Author: Florian Privé [aut, cre],
  Michael Blum [ths],
  Hugues Aschard [ths]
Maintainer: Florian Privé <florian.prive.21@gmail.com>
Repository: CRAN
Date/Publication: 2017-09-02 16:01:40 UTC
