The purpose of the
rgen package is to provide popular sampling distributions
that are not exported by R’s
Math API or available in C++11
and onwards. These samplers are written using armadillo. Please note,
these samplers, just like the ones in armadillo
cannot be used in parallelized code as the underlying
generation routines rely upon R calls that are
single-threaded.
rgenrgen is available on CRAN and GitHub.
To install the package, you must first have a compiler on your system that is compatible with R.
For help on obtaining a compiler consult:
With a compiler in hand, install the package from CRAN with:
or from GitHub by:
rgenThere are two ways to use rgen. The first is to use
rgen in a standalone script. The script is typically built
using sourceCpp(). The second approach allows for
rgen to be used within an R package.
Within the C++ file, the rgen package
provides an Rcpp plugins’ depends statement that must be included after
rgen.h header. This plugin statement indicates that a
dependency is rgen.
#include <RcppArmadillo.h>
// [[Rcpp::depends(RcppArmadillo)]]
#include <rgen.h>
// [[Rcpp::depends(rgen)]]Note: Since rgen relies upon
RcppArmadillo, you must include the
RcppArmadillo.h header and include the traditional
Rcpp dependency attribute,
e.g. // [[Rcpp::depends(RcppArmadillo)]].
For example, the following would allow for you to sample from an inverse wishart distribution:
#include <RcppArmadillo.h>
// [[Rcpp::depends(RcppArmadillo)]]
#include <rgen.h>
// [[Rcpp::depends(rgen)]]
// Surface the riwishart function in the rgen package into R.
// [[Rcpp::export]]
arma::mat riwishart(unsigned int df, const arma::mat& S) {
return rgen::riwishart(df, S);
}
/*** R
# Set seed for reproducibility
set.seed(111)
# Call the C++ function from R
riwishart(3, diag(2))
*/To use rgen in your R package, modify the
DESCRIPTION file by adding:
LinkingTo: Rcpp, RcppArmadillo, rgen
Imports:
Rcpp (>= 0.12.10)
To use C++11, you may wish to add the
following to your src/Makevars and
src/Makevars.win file:
CXX_STD = CXX11