cpp11armadillo: An R Package to Use the Armadillo C++ Library

TL;DR

cpp11armadillo provides a practical bridge enabling R users to leverage Armadillo's C++ linear algebra via cpp11; the paper demonstrates Gauss-Jordan inversion and linear-model routines, including an ordinary least squares estimator $\beta = (X^T X)^{-1} X^T Y$ and a QR-based robust variant, plus a logistic weighted least squares example. It discusses design principles (header-only, vendoring-ready) and contrasts plain cpp11 implementations with Armadillo-powered versions to show concise, faster code. The result is a usable pathway for social scientists and other non-programmers to achieve high-performance linear algebra in R without deep C++ expertise.

Abstract

This article introduces 'cpp11armadillo', a new R package that integrates the powerful Armadillo C++ library for linear algebra into the R programming environment. Targeted primarily at social scientists and other non-programmers, this article explains the computational benefits of moving code to C++ in terms of speed and syntax. We provide a comprehensive overview of Armadillo's capabilities, highlighting its user-friendly syntax akin to MATLAB and its efficiency for computationally intensive tasks. The 'cpp11armadillo' package simplifies a part of the process of using C++ within R by offering additional ease of integration for those who require high-performance linear algebra operations in their R workflows. This work aims to bridge the gap between computational efficiency and accessibility, making advanced linear algebra operations more approachable for R users without extensive programming backgrounds.