Methods operating on rows and columns of matrices, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds().  There are also some vector-based methods, e.g. binMeans(), madDiff() and weightedMedians().  All methods have been optimized for speed and memory usage.

R.rsp, microbenchmark, R.devices, base64enc, ggplot2, knitr

base64enc, ggplot2, knitr, microbenchmark, R.devices, R.rsp
Methods that Apply to Rows and Columns of Matrices (and to
Vectors)
c(
person("Henrik", "Bengtsson", role=c("aut", "cre", "cph"),
email="henrikb@braju.com"),
person("Hector", "Corrada Bravo", role="ctb"),
person("Robert", "Gentleman", role="ctb"),
person("Ola", "Hossjer", role="ctb"),
person("Harris", "Jaffee", role="ctb"),
person("Dongcan", "Jiang", role="ctb"),
person("Peter", "Langfelder", role="ctb"))
Henrik Bengtsson [aut, cre, cph], Hector Corrada Bravo [ctb], Robert Gentleman [ctb], Ola Hossjer [ctb], Harris Jaffee [ctb], Dongcan Jiang [ctb], Peter Langfelder [ctb]

This packages provides methods operating on rows and
columns of matrices.  The objective is that all methods will
optimized for speed and memory.  This package is currently in a
beta phase.  Make sure to read the 'Roadmap' section in the
package help.

Henrik Bengtsson, Harris Jaffee, Robert Gentleman

Henrik Bengtsson, Hector Corrada Bravo, Robert Gentleman, Harris Jaffee
This packages provides methods operating on rows and columns of matrices.  The objective is to have all methods being optimized for speed and memory consumption.

Henrik Bengtsson, Hector Corrada Bravo, Robert Gentleman,
Harris Jaffee
This packages provides methods operating on rows and
columns of matrices.  The objective is to have all methods
being optimized for speed and memory consumption.

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().