## RcppArmadillo: R and Armadillo via Rcpp

### Synopsis

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.

### Status

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.

### Documentation

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.

### Installation

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

Run

`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)