RcppArmadillo 15.4.2-1 on CRAN: Small Upstream Fixes
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) 1293 other packages on CRAN, downloaded 47.8 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 710 times according to Google Scholar.
This versions updates to the 15.4.2 upstream Armadillo release made this week, as well as to included 15.4.1 version we released only to GitHub and r-universe so do not exceed the (roughly) monthly cadence. For this release, we had run the usual complete reverse-dependency check which came back spotless, and did CRAN so no email exchange needed despite nearly 1300 reverse dependencies. Automation can be helpful when used with a well-maintained software stack. The package has also already been updated for Debian, built for r2u, and will build shortly at CRAN for the different binary releases.
All changes since the last CRAN release follow.
Changes in RcppArmadillo version 15.4.2-1 (2026-07-25)
Upgraded to Armadillo release 15.4.2 (Medium Roast Agave)
- Fix speed regressions in
diagvec()anddiagmat()Changes in RcppArmadillo version 15.4.1-1 [github-only] (2026-07-09)
Upgraded to Armadillo release 15.4.1 (Medium Roast Agave)
Fix for rare infinite recursion bug in sparse version of
diagmat()More efficient checks for aliasing
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.
