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 <doi:10.1093/bioinformatics/bty185>.

Version: 1.3.1
Depends: R (≥ 3.3)
Imports: bigassertr (≥ 0.1.1), bigparallelr (≥ 0.2.3), cowplot, foreach, ggplot2 (≥ 3.0), graphics, methods, Rcpp, RSpectra, stats, tibble, utils
LinkingTo: Rcpp, RcppArmadillo, rmio (≥ 0.1.3)
Suggests: biglasso, bigmemory (≥ 4.5.33), bigreadr (≥ 0.2), covr, data.table, dplyr, glmnet, hexbin, memuse, ModelMetrics, RhpcBLASctl, spelling (≥ 1.2), testthat
Published: 2020-11-06
Author: Florian Privé [aut, cre], Michael Blum [ths], Hugues Aschard [ths]
Maintainer: Florian Privé <florian.prive.21 at>
License: GPL-3
NeedsCompilation: yes
Language: en-US
Citation: bigstatsr citation info
Materials: README NEWS
In views: HighPerformanceComputing
CRAN checks: bigstatsr results


Reference manual: bigstatsr.pdf
Package source: bigstatsr_1.3.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: bigstatsr_1.3.1.tgz, r-oldrel: bigstatsr_1.3.1.tgz
Old sources: bigstatsr archive

Reverse dependencies:

Reverse depends: bigsnpr
Reverse imports: bigdist, chickn, Directional, pchc
Reverse linking to: bigsnpr, chickn


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