RcppSMC 0.2.1: A few new tricks

March 18, 2018
By

(This article was first published on Thinking inside the box , and kindly contributed to R-bloggers)

A new release, now at 0.2.1, of the RcppSMC package arrived on CRAN earlier this afternoon (and once again as a very quick pretest-publish within minutes of submission).

RcppSMC provides Rcpp-based bindings to R for the Sequential Monte Carlo Template Classes (SMCTC) by Adam Johansen described in his JSS article. Sequential Monte Carlo is also referred to as Particle Filter in some contexts .

This releases contains a few bug fixes and one minor rearrangment allowing header-only use of the package from other packages, or via a Rcpp plugin. Many of these changes were driven by new contributors, which is a wonderful thing to see for any open source project! So thanks to everybody who helped with. Full details below.

Changes in RcppSMC version 0.2.1 (2018-03-18)

  • The sampler now has a copy constructor and assignment overload (Brian Ni in #28).

  • The SMC library component can now be used in header-only mode (Martin Lysy in #29).

  • Plugin support was added for use via cppFunction() and other Rcpp Attributes (or inline functions (Dirk in #30).

  • The sampler copy ctor/assigment operator is now copy-constructor safe (Martin Lysy In #32).

  • A bug in state variance calculation was corrected (Adam in #36 addressing #34).

  • History getter methods are now more user-friendly (Tiberiu Lepadatu in #37).

  • Use of pow with atomic types was disambiguated to std::pow) to help the Solaris compiler (Dirk in #42).

Courtesy of CRANberries, there is a diffstat report for this release.

More information is on the RcppSMC page. Issues and bugreports should go to the GitHub issue tracker.

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 on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers

Sponsors

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)