This package is hidden from search results because it is not hosted in the universe of the upstream ownerhenrikbengtsson. To fix this you can add URL: https://fastverse.r-universe.dev/matrixStats to the package DESCRIPTION file. See also theR-universe documentation.

Package: matrixStats 1.5.0-9000

Henrik Bengtsson

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 weightedMedian().

Authors:Henrik Bengtsson [aut, cre, cph], Constantin Ahlmann-Eltze [ctb], Hector Corrada Bravo [ctb], Robert Gentleman [ctb], Jan Gleixner [ctb], Peter Hickey [ctb], Ola Hossjer [ctb], Harris Jaffee [ctb], Dongcan Jiang [ctb], Peter Langfelder [ctb], Brian Montgomery [ctb], Angelina Panagopoulou [ctb], Hugh Parsonage [ctb], Jakob Peder Pettersen [ctb]

# Install 'matrixStats' in R:

install.packages('matrixStats', repos = c('https://fastverse.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/henrikbengtsson/matrixstats/issues

On CRAN:

matrix performance vector

18.62 score 215 stars 2.6k packages 24k scripts 816k downloads 46 mentions 102 exports 0 dependencies

Last updated from:6526883660. Checks:11 NOTE, 2 OK. Indexed: no.

Target	Result	Time
linux-devel-arm64	NOTE	203
linux-devel-x86_64	NOTE	232
source / vignettes	OK	198
linux-release-arm64	NOTE	208
linux-release-x86_64	NOTE	220
macos-release-arm64	NOTE	128
macos-release-x86_64	NOTE	373
macos-oldrel-arm64	NOTE	124
macos-oldrel-x86_64	NOTE	362
windows-devel	NOTE	182
windows-release	NOTE	181
windows-oldrel	NOTE	178
wasm-release	OK	105

Exports:allocArray allocMatrix allocVector allValue anyMissing anyValue binCounts binMeans colAlls colAnyMissings colAnyNAs colAnys colAvgsPerRowSet colCollapse colCounts colCummaxs colCummins colCumprods colCumsums colDiffs colIQRDiffs colIQRs colLogSumExps colMadDiffs colMads colMaxs colMeans2 colMedians colMins colOrderStats colProds colQuantiles colRanges colRanks colSdDiffs colSds colSums2 colTabulates colVarDiffs colVars colWeightedMads colWeightedMeans colWeightedMedians colWeightedSds colWeightedVars count diff2 indexByRow iqr iqrDiff logSumExp madDiff mean2 product rowAlls rowAnyMissings rowAnyNAs rowAnys rowAvgsPerColSet rowCollapse rowCounts rowCummaxs rowCummins rowCumprods rowCumsums rowDiffs rowIQRDiffs rowIQRs rowLogSumExps rowMadDiffs rowMads rowMaxs rowMeans2 rowMedians rowMins rowOrderStats rowProds rowQuantiles rowRanges rowRanks rowSdDiffs rowSds rowSums2 rowTabulates rowVarDiffs rowVars rowWeightedMads rowWeightedMeans rowWeightedMedians rowWeightedSds rowWeightedVars sdDiff signTabulate sum2 t_tx_OP_y varDiff weightedMad weightedMean weightedMedian weightedSd weightedVar x_OP_y

Dependencies:

matrixStats: Summary of functions

Rendered frommatrixStats-methods.md.rspusingR.rsp::rsp

Last update: 2019-07-21
Started: 2014-12-20

Help page	Topics
Package matrixStats	matrixStats-package matrixStats
Checks if there are any missing values in an object or not	anyMissing colAnyMissings colAnyNAs rowAnyMissings rowAnyNAs
Fast element counting in non-overlapping bins	binCounts
Fast mean calculations in non-overlapping bins	binMeans
Translates matrix indices by rows into indices by columns	indexByRow
Accurately computes the logarithm of the sum of exponentials	logSumExp
Calculates the product for each row (column) in a matrix	colProds product rowProds
Checks if a value exists / does not exist in each row (column) of a matrix	allValue anyValue colAlls colAnys rowAlls rowAnys
Extracts one cell per row (column) from a matrix	colCollapse rowCollapse
Counts the number of occurrences of a specific value	colCounts count rowCounts
Cumulative sums, products, minima and maxima for each row (column) in a matrix	colCummaxs colCummins colCumprods colCumsums rowCummaxs rowCummins rowCumprods rowCumsums
Calculates difference for each row (column) in a matrix	colDiffs rowDiffs
Estimates of the interquartile range for each row (column) in a matrix	colIQRs iqr rowIQRs
Accurately computes the logarithm of the sum of exponentials across rows or columns	colLogSumExps rowLogSumExps
Standard deviation estimates for each row (column) in a matrix	colMads colSds rowMads rowSds
Calculates the mean for each row (column) in a matrix	colMeans2 rowMeans2
Calculates the median for each row (column) in a matrix	colMedians rowMedians
Gets an order statistic for each row (column) in a matrix	colOrderStats rowOrderStats
Estimates quantiles for each row (column) in a matrix	colQuantiles rowQuantiles
Gets the range of values in each row (column) of a matrix	colMaxs colMins colRanges rowMaxs rowMins rowRanges
Gets the rank of the elements in each row (column) of a matrix	colRanks rowRanks
Calculates the sum for each row (column) in a matrix	colSums2 rowSums2
Tabulates the values in a matrix by row (column).	colTabulates rowTabulates
Variance estimates for each row (column) in a matrix	colVars rowVars
Calculates the weighted means for each row (column) in a matrix	colWeightedMeans rowWeightedMeans
Calculates the weighted medians for each row (column) in a matrix	colWeightedMedians rowWeightedMedians
Estimation of scale based on sequential-order differences	colIQRDiffs colMadDiffs colSdDiffs colVarDiffs iqrDiff madDiff rowIQRDiffs rowMadDiffs rowSdDiffs rowVarDiffs sdDiff varDiff
Weighted Median Absolute Deviation (MAD)	colWeightedMads rowWeightedMads weightedMad
Weighted Arithmetic Mean	weightedMean
Weighted Median Value	weightedMedian
Weighted variance and weighted standard deviation	colWeightedSds colWeightedVars rowWeightedSds rowWeightedVars weightedSd weightedVar

Package: matrixStats 1.5.0-9000

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

Citation

Development and contributors

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)