UPDATE: Students, please see our Google Summer of Code 2015 project Subsetted and parallel computations in matrixStats for further enhancements of the matrixStats package. Application deadline is March 27, 2015.
The matrixStats package provides highly optimized functions for
computing common summaries over rows and columns of matrices,
e.g. rowQuantiles(). There are also functions that operate on vectors,
e.g. logSumExp(). Their implementations strive to minimize both memory
usage and processing time. They are often remarkably faster compared
to good old apply() solutions. The calculations are mostly implemented
in C, which allow us to optimize beyond what is possible to do in
plain R. The package installs out-of-the-box on all common operating
systems, including Linux, OS X and Windows.
It is many times faster to calculate medians column by column using
> library("matrixStats")
> X <- matrix(rnorm(20 * 500), nrow = 20, ncol = 500)
> mu <- colMedians(X)compared with
> mu <- apply(X, MARGIN=2, FUN=medians)For formal benchmarking of matrixStats functions relative to alternatives, see the Benchmark reports.
R package matrixStats is available on CRAN and can be installed in R as:
install.packages('matrixStats')| Resource: | CRAN | Travis CI | Appveyor |
|---|---|---|---|
| Platforms: | Multiple | Linux | Windows |
| R CMD check | status |  |
|
| Test coverage |  |