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, macOS and Windows.

With a matrix

```
> x <- matrix(rnorm(20 * 500), nrow = 20, ncol = 500)
```

it is many times faster to calculate medians column by column using

```
> mu <- matrixStats::colMedians(x)
```

than using

```
> mu <- apply(x, MARGIN = 2, FUN = median)
```

Moreover, if performing calculations on a subset of rows and/or columns, using

```
> mu <- colMedians(x, rows = 33:158, cols = 1001:3000)
```

is much faster and more memory efficient than

```
> mu <- apply(x[33:158, 1001:3000], MARGIN = 2, FUN = median)
```

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")
```

To install the pre-release version that is available in Git branch `develop`

on GitHub, use:

```
remotes::install_github("HenrikBengtsson/matrixStats", ref="develop")
```

This will install the package from source. Because of this and because this package also compiles native code, Windows users need to have Rtools installed and macOS users need to have Xcode installed.

To contribute to this package, please see CONTRIBUTING.md.

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