RcppArmadillo: R and Armadillo via Rcpp

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RcppArmadillo provides an interface from R to and from Armadillo by utilising the Rcpp R/C++ interface library.

What is 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 deliberately similar to Matlab (TM). See its website more information about Armadillo.

So give me an example!

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

#include <RcppArmadillo.h>
// [[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

    // std.errors of coefficients
    double s2 = std::inner_product(res.begin(), res.end(), res.begin(), 0.0)/(n - k);

    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() the file above to compile the function. A slightly more involved version is also included in the package as the fastLm() function.


The package is under active development with releases to CRAN about once every other month, and widely-used by other CRAN packages as can be seen from the CRAN package page. As of September 2019, there are 658 CRAN packages using RcppArmadillo.


The package contains a pdf vignette which is a pre-print of the paper by Eddelbuettel and Sanderson in CSDA (2014), as well as an introductory vignette for the sparse matrix conversions.


RcppArmadillo is a CRAN package, and lives otherwise in its own habitat on GitHub within the RcppCore GitHub organization.



to install from your nearest CRAN mirror.


Dirk Eddelbuettel, Romain Francois, Doug Bates and Binxiang Ni


GPL (>= 2)