Rcpp.org Website Review

This page provides a few pointers to other popular packages using Rcpp, as well as to a few related external sites. Rcpp provides a powerful API on top of R, permitting direct interchange of rich R objects (including S3, S4 or Reference Clas* objects) between R and C++. Rcpp sugar gives syntactic sugar such as vectorised C++ expression; Rcpp modules provide easy extensibility using declarations and Rcpp attributes greatly facilitates code integration. good balance between speed and ease of use, and its syntax is deliberately similar to Matlab which makes it easy to port existing templated, and highly optimised. It provides a wide variety of matrix methods, various decompositions and includes support for sparse RInside makes it easy to use R from inside another C++ by wrapping the existing R embedding API in an easy-to-use C++ clas*. Over a dozen basic example are included in the package, as well as more specialised example showing use of RInside with MPI for parallel computing, Qt for cross-platform GUIs, Wt for web applications, as well as the Armadillo and Eigen templated C++ libraries for linear algebras. See more on the A small selection of packages which use Rcpp follows below. These are in most case small packages which can provides examples to build upon. illustrates the usefulness of Rcpp for modern simulation-based methods. RcppDE is a port of (an older version of) the DEoptim package. Converting from C to C++ reduced the code from 700 lines to 400 lines making it easier to deploy and extend. We also use Rcpp to allow a compiled objective function to be pas*ed in for the optimization. RcppCNPy is small single-purpose package which wraps around a small standalone C++ library to read and write Python NumPy files---so that