matrixStats: Functions that Apply to Rows and Columns of Matrices (and to Vectors)

High-performing functions operating on rows and columns of matrices, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds(). Functions optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized. There are also optimized vector-based methods, e.g. binMeans(), madDiff() and weightedMedians().

Version: 0.50.1
Depends: R (≥ 2.12.0)
Imports: methods
Suggests: base64enc, ggplot2, knitr, microbenchmark, R.devices, R.rsp
Published: 2015-12-15
Author: Henrik Bengtsson [aut, cre, cph], Hector Corrada Bravo [ctb], Robert Gentleman [ctb], Ola Hossjer [ctb], Harris Jaffee [ctb], Dongcan Jiang [ctb], Peter Langfelder [ctb]
Maintainer: Henrik Bengtsson <henrikb at>
License: Artistic-2.0
NeedsCompilation: yes
Materials: NEWS
CRAN checks: matrixStats results


Reference manual: matrixStats.pdf
Vignettes: matrixStats: Summary of functions
Package source: matrixStats_0.50.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: matrixStats_0.50.1.tgz, r-oldrel: matrixStats_0.14.0.tgz
OS X Mavericks binaries: r-release: matrixStats_0.50.1.tgz
Old sources: matrixStats archive

Reverse dependencies:

Reverse depends: aSPU, DAMOCLES, FastHCS, FastPCS, FastRCS, GAD, localgauss, LS2Wstat, NSA, r2dRue, samr, ttScreening, visualFields
Reverse imports: ACNE, aroma.affymetrix,, aroma.core, bdynsys, bingat, bnclassify, calmate, carx, dplR, fslr, loo, Luminescence, MFHD, mmtfa, peakPick, PSCBS, randomizationInference, SemiParBIVProbit, SGP, statar, stm, WGCNA
Reverse suggests: MetaQC, MPAgenomics, tmlenet