https://github.com/rcppcore/rcpparmadillo

Rcpp integration for the Armadillo templated linear algebra library
https://github.com/rcppcore/rcpparmadillo

armadillo c-plus-plus r r-package rcpp rcpparmadillo

Last synced: 4 days ago
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Rcpp integration for the Armadillo templated linear algebra library

• Host: GitHub
• URL: https://github.com/rcppcore/rcpparmadillo
• Owner: RcppCore
• Created: 2013-11-02T18:33:00.000Z (over 11 years ago)
• Default Branch: master
• Last Pushed: 2025-04-26T11:51:51.000Z (22 days ago)
• Last Synced: 2025-05-13T22:51:36.826Z (4 days ago)
• Topics: armadillo, c-plus-plus, r, r-package, rcpp, rcpparmadillo
• Language: C++
• Homepage:
• Size: 10.8 MB
• Stars: 202
• Watchers: 19
• Forks: 56
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • Changelog: ChangeLog

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README

        

## RcppArmadillo: R and Armadillo via Rcpp

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[![CSDA](https://img.shields.io/badge/CSDA-10.1016%2Fj.csda.2013.02.005-brightgreen)](https://doi.org/10.1016/j.csda.2013.02.005)

### Synopsis

RcppArmadillo provides an interface from R to and from [Armadillo][armadillo] by utilising the [Rcpp

R/C++ interface library][rcpp].

### What is Armadillo?

[Armadillo][armadillo] is a high-quality linear algebra library for the C++ language, aiming towards

a good balance between speed and ease of use. It provides high-level syntax and

[functionality](https://arma.sourceforge.net/docs.html) deliberately similar to Matlab (TM).  See

[its website][armadillo] more information about Armadillo.

### So give me an example!

Glad you asked. Here is a light-weight and fast implementation of linear regression:

```c++

#include 

// [[Rcpp::depends(RcppArmadillo)]]

// [[Rcpp::export]]

Rcpp::List fastLm(const arma::mat& X, const arma::colvec& y) {

    int n = X.n_rows, k = X.n_cols;

    arma::colvec coef = arma::solve(X, y);     // fit model y ~ X

    arma::colvec res  = y - X*coef;            // residuals

    double s2 = arma::dot(res, res) / (n - k); // std.errors of coefficients

    arma::colvec std_err = arma::sqrt(s2 * arma::diagvec(arma::pinv(arma::trans(X)*X)));

    return Rcpp::List::create(Rcpp::Named("coefficients") = coef,

                              Rcpp::Named("stderr")       = std_err,

                              Rcpp::Named("df.residual")  = n - k);

}

```

You can

[`Rcpp::sourceCpp()`](https://cran.r-project.org/package=Rcpp/vignettes/Rcpp-attributes.pdf)

the file above to compile the function.  A version is also included in the

package [as the `fastLm()`](https://github.com/RcppCore/RcppArmadillo/blob/master/R/fastLm.R)

function.

The `RcppArmadillo/Lighter` header includes [Rcpp][rcpp] via its `Rcpp/Lighter` header which

precludes some more compile-time heavy features such as 'Rcpp Modules' which we may not need. See

the [Rcpp][rcpp] docs more details about 'Light', 'Lighter' and 'Lightest'.  In the example above,

the switch saves about 15% of total compilation time.

### Status

The package is mature yet under active development with releases to [CRAN][cran] about once every

other month, and widely-used by other CRAN packages as can be seen from the [CRAN package page][cran

pkg].  As of April 2024, there are 1135 CRAN packages using RcppArmadillo.

### Documentation

The package contains a pdf vignette which is a pre-print of the

[paper by Eddelbuettel and Sanderson](http://dx.doi.org/10.1016/j.csda.2013.02.005)

in CSDA (2014), as well as an introductory vignette for the sparse

matrix conversions.

### Installation

RcppArmadillo is a [CRAN package][cran pkg], and lives otherwise in its own habitat on

[GitHub](https://github.com/RcppCore/RcppArmadillo) within the

[RcppCore](https://github.com/RcppCore) GitHub organization.

Run

```r

install.packages("RcppArmadillo")

```

to install from your nearest CRAN mirror.

### Authors

Dirk Eddelbuettel, Romain Francois, Doug Bates, Binxiang Ni, and Conrad Sanderson

### License

GPL (>= 2)

[armadillo]: https://arma.sourceforge.net

[rcpp]: https://www.rcpp.org

[cran]: https://cran.r-project.org

[cran pkg]: https://cran.r-project.org/package=RcppArmadillo