A new major released of Armadillo came out earlier today. I prepared the corresponding RcppArmadillo package 0.3.4.0 which also arrived on CRAN earlier today. This released contains a few performance improvements, the beginnings of support of sparse matrices and more, see below. We also post the NEWS entry for the beta release which was prepared, but not uploaded to CRAN to minimise the upload frequency there. On the RcppArmadillo side, two enhancements were made for the fastLm() function for faster linear model fits.

Changes in RcppArmadillo version 0.3.4.0 (2012-09-06)

• Upgraded to Armadillo release 3.4.0 (Ku De Ta)

  • added economical QR decomposition: qr_econ()

  • added .each_col() & .each_row() for vector operations repeated on each column or row

  • added preliminary support for sparse matrices, contributed by Ryan Curtin et al. (Georgia Institute of Technology)

  • faster singular value decomposition via divide-and-conquer algorithm

  • faster .randn()

• NEWS file converted to Rd format

Changes in RcppArmadillo version 0.3.3.91 (2012-08-30)

• Upgraded to Armadillo release 3.3.91

  • faster singular value decomposition via “divide and conquer” algorithm

  • added economical QR decomposition: qr_econ()

  • added .each_col() & .each_row() for vector operations repeated on each column or row

  • added preliminary support for sparse matrices, contributed by Ryan Curtin, James Cline and Matthew Amidon (Georgia Institute of Technology)

• Corrected summary method to deal with the no intercept case when using a formula; also display residual summary() statistics

• Expanded unit tests for fastLm

Courtesy of CRANberries, there is also a diffstat report for 0.3.4.0 relative to 0.3.2.4 As always, more detailed information is on the RcppArmadillo page. Questions, comments etc should go to the rcpp-devel mailing list off the R-Forge page.