RcppDE 0.1.6

[This article was first published on Thinking inside the box , and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Another maintenance release, now at version 0.1.6, of our RcppDE package is now on CRAN. It follows the most recent (unblogged, my bad) 0.1.5 release in January 2016 and the 0.1.4 release in September 2015.

RcppDE is a “port” of DEoptim, a popular package for derivative-free optimisation using differential evolution optimization, to C++. By using RcppArmadillo, the code becomes a lot shorter and more legible. Our other main contribution is to leverage some of the excellence we get for free from using Rcpp, in particular the ability to optimise user-supplied compiled objective functions which can make things a lot faster than repeatedly evaluating interpreted objective functions as DEoptim (and, in fairness, just like most other optimisers) does.

That is also what lead to this upload: Kyle Baron noticed an issue when nesting a user-supplied compiled function inside a user-supplied compiled objective function — and when using the newest Rcpp. This has to do with some cleanups we made for how RNG state is, or is not, set and preserved. Kevin Ushey was (once again) a real trooper here and added a simple class to Rcpp (in what is now the development version 0.12.17.2 available on the Rcpp drat repo) and used that here to (selectively) restore behaviour similarly to what we had in Rcpp (but which created another issue for another project). So all that is good now in all use cases. We also have some other changes contributed by Yi Kang some time ago for both JADE style randomization and some internal tweaks. Some packaging details were updated, and that sums up release 0.1.6.

Courtesy of CRANberries, there is also a diffstat report for the most recent release.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

To leave a comment for the author, please follow the link and comment on their blog: Thinking inside the box .

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)