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 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) 978 other packages on CRAN, downloaded over 24 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 469 times according to Google Scholar.
This release brings a first new upstream fix in the new release series 11.*. In particular, treatment of ill-conditioned matrices is further strengthened. We once again tested this very rigorously via three different RC releases each of which got a full reverse-dependencies run (for which results are always logged here). A minor issue with old
g++ compilers was found once 11.1.0 was tagged to this upstream release is now 11.1.1. Also fixed is an OpenMP setup issue where Justin Silverman noticed that we did not propagate the
-fopenmp setting correctly.
The full set of changes (since the last CRAN release 0.11.0.0.0) follows.
Changes in RcppArmadillo version 0.11.1.1.0 (2022-05-15)
Upgraded to Armadillo release 11.1.1 (Angry Kitchen Appliance)
inv_sympd()to disallow inverses of poorly conditioned matrices
more efficient handling of rank-deficient matrices via
better detection of rank deficient matrices by
faster handling of symmetric and diagonal matrices by
Changes in RcppArmadillo version 0.11.0.1.0 (2022-04-14)
Upgraded to Armadillo release 11.0.1 (Creme Brulee)
- fix miscompilation of
inv_sympd()functions when using
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 R-Forge page.
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