Wed, 17 Dec 2025

RcppArmadillo 15.2.3-1 on CRAN: Upstream Update

armadillo image

Armadillo is a powerful and expressive C++ template library for linear algebra and scientific computing. It aims towards a good balance between speed and ease of use, has a syntax deliberately close to Matlab, and is useful for algorithm development directly in C++, or quick conversion of research code into production environments. RcppArmadillo integrates this library with the R environment and language–and is widely used by (currently) 1272 other packages on CRAN, downloaded 43.2 million times (per the partial logs from the cloud mirrors of CRAN), and the CSDA paper (preprint / vignette) by Conrad and myself has been cited 661 times according to Google Scholar.

This versions updates to the 15.2.3 upstream Armadillo release from yesterday. It brings minor changes over the RcppArmadillo 15.2.2 release made last month (and described in this post). As noted previously, and due to both the upstream transition to C++14 coupled with the CRAN move away from C++11, the package offers a transition by allowing packages to remain with the older, pre-15.0.0 ‘legacy’ Armadillo yet offering the current version as the default. If and when CRAN will have nudged (nearly) all maintainers away from C++11 (and now also C++14 !!) we can remove the fallback. Our offer to help with the C++ modernization still stands, so please get in touch if we can be of assistance. As a reminder, the meta-issue #475 regroups all the resources for the C++11 transition.

There were no R-side changes in this release. The detailed changes since the last release follow.

Changes in RcppArmadillo version 15.2.3-1 (2025-12-16)

  • Upgraded to Armadillo release 15.2.3 (Medium Roast Deluxe)

    • Faster .resize() for vectors

    • Faster repcube()

Courtesy of my CRANberries, there is a diffstat report relative to previous release. More detailed information is on the RcppArmadillo page. Questions, comments etc should go to the rcpp-devel mailing list off the Rcpp R-Forge page.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. If you like this or other open-source work I do, you can sponsor me at GitHub.

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